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A 10-year-old boy with ‘voices in my head’: Is it a psychotic disorder?

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A 10-year-old boy with ‘voices in my head’: Is it a psychotic disorder?

CASE Auditory hallucinations?

M, age 10, has had multiple visits to the pediatric emergency department (PED) with the chief concern of excessive urinary frequency. At each visit, the medical workup has been negative and he was discharged home. After a few months, M’s parents bring their son back to the PED because he reports hearing “voices in my head” and “feeling tense and scared.” When these feelings become too overwhelming, M stops eating and experiences substantial fear and anxiety that require his mother’s repeated reassurances. M’s mother reports that 2 weeks before his most recent PED visit, he became increasingly anxious and disturbed, and said he was afraid most of the time, and worried about the safety of his family for no apparent reason.

The psychiatrist evaluates M in the PED and diagnoses him with unspecified schizophrenia spectrum and other psychotic disorder based on his persistent report of auditory and tactile hallucinations, including hearing a voice of a man telling him he was going to choke on his food and feeling someone touch his arm to soothe him during his anxious moments. M does not meet criteria for acute inpatient hospitalization, and is discharged home with referral to follow-up at our child and adolescent psychiatry outpatient clinic.

On subsequent evaluation in our clinic, M reports most of the same about his experience hearing “voices in my head” that repeatedly suggest “I might choke on my food and end up seriously ill in the hospital.” He started to hear the “voices” after he witnessed his sister choke while eating a few days earlier. He also mentions that the “voices” tell him “you have to use the restroom.” As a result, he uses the restroom several times before leaving for home and is frequently late for school. His parents accommodate his behavior—his mother allows him to use the bathroom multiple times, and his father overlooks the behavior as part of school anxiety.

At school, his teacher reports a concern for attention-deficit/hyperactivity disorder (ADHD) based on M’s continuous inattentiveness in class and dropping grades. He asks for bathroom breaks up to 15 times a day, which disrupts his class work.

These behaviors have led to a gradual 1-year decline in his overall functioning, including difficulty at school for requesting too many bathroom breaks; having to repeat the 3rd grade; and incurring multiple hospital visits for evaluation of his various complaints. M has become socially isolated and withdrawn from friends and family.

M’s developmental history is normal and his family history is negative for any psychiatric disorder. Medical history and physical examination are unremarkable. CT scan of his head is unremarkable, and all hematologic and biochemistry laboratory test values are within normal range.

[polldaddy:9971376]

 

Continue to: The authors' observations

 

 

The authors’ observations

Several factors may contribute to an increased chance of misdiagnosis of a psychiatric illness, especially when evaluating children. Compared with adults, children have a limited ability to explain their symptoms, and given their limited cognitive capacity, they may have difficulty identifying their symptoms as functionally limiting. A comprehensive clinical evaluation, including detailed interviews with the patient, the patient’s parents, and if possible, the patient’s teachers, is required to assess the child’s symptomatology and make an accurate clinical diagnosis.

On closer sequential evaluations with M and his family, we determined that the “voices” he was hearing were actually intrusive thoughts, and not hallucinations. M clarified this by saying that first he feels a “pressure”-like sensation in his head, followed by repeated intrusive thoughts of voiding his bladder that compel him to go to the restroom to try to urinate. He feels temporary relief after complying with the urge, even when he passes only a small amount of urine or just washes his hands. After a brief period of relief, this process repeats itself. Further, he was able to clarify his experience while eating food, where he first felt a “pressure”-like sensation in his head, followed by intrusive thoughts of choking that result in him not eating.

This led us to a more appropriate diagnosis of OCD (Table 11). The incidence of OCD has 2 peaks, with different gender distributions. The first peak occurs in childhood, with symptoms mostly arising between 7 and 12 years of age and affecting boys more often than girls. The second peak occurs in early adulthood, at a mean age of 21 years, with a slight female majority.2 However, OCD is often under recognized and undertreated, perhaps due to its extensive heterogeneity; symptom presentations and comorbidity patterns can vary noticeably between individual patients as well as age groups.

 

OCD is characterized by the presence of obsessions or compulsions that wax and wane in severity, are time-consuming (at least 1 hour per day), and cause subjective distress or interfere with life of the patient or the family. Adults with OCD recognize at some level that the obsessions and/or compulsions are excessive and unreasonable, although children are not required to have this insight to meet criteria for the diagnosis.1 Rating scales, such as the Children’s Yale-Brown Obsessive-Compulsive Scale, Dimensional Yale-Brown Obsessive-Compulsive Scale, and Family Accommodation Scale, are useful to obtain detailed information regarding OCD symptoms, tics, and other factors relevant to the diagnosis.

Continue to: M's symptomatology...

 

 

M’s symptomatology did not appear to be psychotic. He was screened for positive or negative symptoms of psychosis, which he and his family clearly denied. Moreover, M’s compulsions (going to the restroom) were typically performed in response to his obsessions (urge to void his bladder) to reduce his distress, which is different from schizophrenia, in which repetitive behaviors are performed in response to psychotic ideation, and not obsessions (Table 23-5).

M’s inattentiveness in the classroom was found to be related to his obsessions and compulsions, and not part of a symptom cluster characterizing ADHD. Teachers often interpret inattention and poor classroom performance as ADHD, but having detailed conversations with teachers often is helpful in understanding the nature of a child’s symptomology and making the appropriate diagnosis.

 

Establishing the correct clinical diagnosis is critical because it is the starting point in treatment. First-line medication for one condition may exacerbate the symptoms of others. For example, in addition to having a large adverse-effect burden, antipsychotics can induce de novo obsessive–compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors (SSRIs) may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.6 Similarly, stimulant medications for ADHD may exacerbate OCS and may even induce them on their own.7,8

[polldaddy:9971377]

 

Continue to: The authors' observations

 

 

The authors’ observations

Studies have reported an average of 2.5 years from the onset of OCD symptoms to diagnosis in the United States.9 A key reason for this delay, which is more frequently encountered in pediatric patients, is secrecy. Children often feel embarrassed about their symptoms and conceal them until the interference with their functioning becomes extremely disabling. In some cases, symptoms may closely resemble normal childhood routines. In fact, some repetitive behaviors may be normal in some developmental stages, and OCD could be conceptualized as a pathological condition with continuity of normal behaviors during different developmental periods.10

 

Also, symptoms may go unnoticed for quite some time as unsuspecting and well-intentioned parents and family members become overly involved in the child’s rituals (eg, allowing for increasing frequent prolonged bathroom breaks or frequent change of clothing, etc.). This well-established phenomenon, termed accommodation, is defined as participation of family members in a child’s OCD–related rituals.11 Especially when symptoms are mild or the child is functioning well, accommodation can make it difficult for parents to realize the presence or nature of a problem, as they might tend to minimize their child’s symptoms as representing a unique personality trait or a special “quirk.” Parents generally will seek treatment when their child’s symptoms become more impairing and begin to interfere with social functioning, school performance, or family functioning.

The clinical picture is further complicated by comorbidity. Approximately 60% to 80% of children and adolescents with OCD have ≥1 comorbid psychiatric disorders. Some of the most common include tic disorders, ADHD, anxiety disorders, and mood or eating disorders.9

[polldaddy:9971379]

 

Continue to: TREATMENT Combination therapy

 

 

TREATMENT Combination therapy

In keeping with American Academy of Child and Adolescent Psychiatry guidelines on treating OCD (Table 312), we start M on fluoxetine 10 mg/d. He also begins CBT. Fluoxetine is slowly titrated to 40 mg/d while M engages in learning and utilizing CBT techniques to manage his OCD.

The authors’ observations

The combination of CBT and medication has been suggested as the treatment of choice for moderate and severe OCD.12 The Pediatric OCD Treatment Study, a 5-year, 3-site outcome study designed to compare placebo, sertraline, CBT, and combined CBT and sertraline, concluded that the combined treatment (CBT plus sertraline) was more effective than CBT alone or sertraline alone.13 The effect sizes for the combined treatment, CBT alone, and sertraline alone were 1.4, 0.97, and 0.67, respectively. Remission rates for SSRIs alone are <33%.13,14

SSRIs are the first-line medication for OCD in children, adolescents, and adults (Table 312). Well-designed clinical trials have demonstrated the efficacy and safety of the SSRIs fluoxetine, sertraline, and fluvoxamine (alone or combined with CBT) in children and adolescents with OCD.13 Other SSRIs, such as citalopram, paroxetine, and escitalopram, also have demonstrated efficacy in children and adolescents with OCD, even though the FDA has not yet approved their use in pediatric patients.12 Despite a positive trial of paroxetine in pediatric OCD,12 there have been concerns related to its higher rates of treatment-emergent suicidality,15 lower likelihood of treatment response,16 and its particularly short half-life in pediatric patients.17

Clomipramine is a tricyclic antidepressant with serotonergic properties that is used alone or to boost the effect of an SSRI when there is a partial response. It should be introduced at a low dose in pediatric patients (before age 12) and closely monitored for anticholinergic and cardiac adverse effects. A systemic review and meta-analysis of early treatment responses of SSRIs and clomipramine in pediatric OCD indicated that the greatest benefits occurred early in treatment.18 Clomipramine was associated with a greater measured benefit compared with placebo than SSRIs; there was no evidence of a relationship between SSRI dosing and treatment effect, although data were limited. Adults and children with OCD demonstrated a similar degree and time course of response to SSRIs in OCD.18

Treatment should start with a low dose to reduce the risk of adverse effects with an adequate trial for 10 to 16 weeks at adequate doses. Most experts suggest that treatment should continue for at least 12 months after symptom resolution or stabilization, followed by a very gradual cessation.19

Continue to: OUTCOME Improvement in functioning

 

 

OUTCOME Improvement in functioning

After 12 months of combined CBT and fluoxetine, M’s global assessment of functioning (GAF) scale score improves from 35 to 80, indicating major improvement in overall functional level.

Acknowledgement

The authors thank Uzoma Osuchukwu, MD, ex-fellow, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York, for his assistance with this article.

 

 

Bottom Line

Obsessive-compulsive disorder may masquerade as a schizophrenia spectrum disorder, particularly in younger patients. Accurate differentiation is crucial because antipsychotics can induce de novo obsessive-compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.

Related Resource

  • Raveendranathan D, Shiva L, Sharma E, et al. Obsessive compulsive disorder masquerading as psychosis. Indian J Psychol Med. 2012;34(2):179-180.  

Drug Brand Names

Citalopram Celexa
Clomipramine Anafranil
Escitalopram Lexapro
Fluoxetine Prozac
Fluvoxamine Luvox
Paroxetine Paxil
Sertraline Zoloft

References

1. Diagnostic and statistical manual of mental disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.
2. Geller D, Biederman J, Jones J, et al. Is juvenile obsessive-compulsive disorder a developmental subtype of the disorder? A review of the pediatric literature. J Am Acad Child Adolesc Psychiatry.1998;37(4):420-427.
3. Huppert JD, Simpson HB, Nissenson KJ, et al. Quality of life and functional impairment in obsessive-compulsive disorder: A comparison of patients with and without comorbidity, patients in remission, and healthy controls. Depress Anxiety. 2009;26(1):39-45.
4. Sobel W, Wolski R, Cancro R, et al. Interpersonal relatedness and paranoid schizophrenia. Am J Psychiatry.1996;153(8):1084-1087.
5. Meares A. The diagnosis of prepsychotic schizophrenia. Lancet. 1959;1(7063):55-58.
6. Poyurovsky M, Weizman A, Weizman R. Obsessive-compulsive disorder in schizophrenia: Clinical characteristics and treatment. CNS Drugs. 2004;18(14):989-1010.
7. Kouris S. Methylphenidate-induced obsessive-compulsiveness. J Am Acad Child Adolesc Psychiatry. 1998;37(2):135.
8. Woolley JB, Heyman I. Dexamphetamine for obsessive-compulsive disorder. Am J Psychiatry. 2003;160(1):183.
9. Geller DA. Obsessive-compulsive and spectrum disorders in children and adolescents. Psychiatr Clin N Am. 2006;29(2):352-370.
10. Evans DW, Milanak ME, Medeiros B, et al. Magical beliefs and rituals in young children. Child Psychiatry Hum Dev. 2002;33(1):43-58.
11. Amir N, Freshman M, Foa E. Family distress and involvement in relatives of obsessive-compulsive disorder patients. J Anxiety Disord. 2000;14(3):209-217.
12. Practice parameter for the assessment and treatment of children and adolescents with obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2012;51(1):98-113.
13. Pediatric OCD Treatment Study (POTS) Team. Cognitive-behavior therapy, sertraline, and their combination for children and adolescents with obsessive-compulsive disorder: The Pediatric OCD Treatment Study (POTS) randomized controlled trial. JAMA. 2004;292(16):1969-1976.
14. Franklin ME, Sapyta J, Freeman JB, et al. Cognitive behavior therapy augmentation of pharmacotherapy in pediatric obsessive-compulsive disorder: The Pediatric OCD Treatment Study II (POTS II) randomized controlled trial. JAMA. 2011;306(11):1224-1232.
15. Wagner KD, Asarnow JR, Vitiello B, et al. Out of the black box: treatment of resistant depression in adolescents and the antidepressant controversy. J Child Adolesc Psychopharmacol. 2012;22(1):5-10.
16. Sakolsky DJ, Perel JM, Emslie GJ, et al. Antidepressant exposure as a predictor of clinical outcomes in the treatment of resistant depression in adolescents (TORDIA) study. J Clin Psychopharmacol. 2011;31(1):92-97.
17. Findling RL. How (not) to dose antidepressants and antipsychotics for children. Current Psychiatry. 2007;6(6):79-83.
18. Varigonda AL, Jakubovski E, Bloch MH. Systematic review and meta-analysis: early treatment responses of selective serotonin reuptake inhibitors and clomipramine in pediatric obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2016 Oct;55(10):851-859.e2.
19. Mancuso E, Faro A, Joshi G, et al. Treatment of pediatric obsessive-compulsive disorder: a review. J Child Adolesc Psychopharmacol. 2010;20(4):299-308.

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Author and Disclosure Information

Dr. Nagi is a PGY-5 child and adolescent psychiatry fellow, and Dr. Somvanshi is a PGY-1 psychiatry resident, Department of Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York. Dr. Reliford is Director and Chief of Service, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York.

Disclosures
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

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Dr. Nagi is a PGY-5 child and adolescent psychiatry fellow, and Dr. Somvanshi is a PGY-1 psychiatry resident, Department of Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York. Dr. Reliford is Director and Chief of Service, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York.

Disclosures
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

Author and Disclosure Information

Dr. Nagi is a PGY-5 child and adolescent psychiatry fellow, and Dr. Somvanshi is a PGY-1 psychiatry resident, Department of Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York. Dr. Reliford is Director and Chief of Service, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York.

Disclosures
The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

Article PDF
Article PDF

CASE Auditory hallucinations?

M, age 10, has had multiple visits to the pediatric emergency department (PED) with the chief concern of excessive urinary frequency. At each visit, the medical workup has been negative and he was discharged home. After a few months, M’s parents bring their son back to the PED because he reports hearing “voices in my head” and “feeling tense and scared.” When these feelings become too overwhelming, M stops eating and experiences substantial fear and anxiety that require his mother’s repeated reassurances. M’s mother reports that 2 weeks before his most recent PED visit, he became increasingly anxious and disturbed, and said he was afraid most of the time, and worried about the safety of his family for no apparent reason.

The psychiatrist evaluates M in the PED and diagnoses him with unspecified schizophrenia spectrum and other psychotic disorder based on his persistent report of auditory and tactile hallucinations, including hearing a voice of a man telling him he was going to choke on his food and feeling someone touch his arm to soothe him during his anxious moments. M does not meet criteria for acute inpatient hospitalization, and is discharged home with referral to follow-up at our child and adolescent psychiatry outpatient clinic.

On subsequent evaluation in our clinic, M reports most of the same about his experience hearing “voices in my head” that repeatedly suggest “I might choke on my food and end up seriously ill in the hospital.” He started to hear the “voices” after he witnessed his sister choke while eating a few days earlier. He also mentions that the “voices” tell him “you have to use the restroom.” As a result, he uses the restroom several times before leaving for home and is frequently late for school. His parents accommodate his behavior—his mother allows him to use the bathroom multiple times, and his father overlooks the behavior as part of school anxiety.

At school, his teacher reports a concern for attention-deficit/hyperactivity disorder (ADHD) based on M’s continuous inattentiveness in class and dropping grades. He asks for bathroom breaks up to 15 times a day, which disrupts his class work.

These behaviors have led to a gradual 1-year decline in his overall functioning, including difficulty at school for requesting too many bathroom breaks; having to repeat the 3rd grade; and incurring multiple hospital visits for evaluation of his various complaints. M has become socially isolated and withdrawn from friends and family.

M’s developmental history is normal and his family history is negative for any psychiatric disorder. Medical history and physical examination are unremarkable. CT scan of his head is unremarkable, and all hematologic and biochemistry laboratory test values are within normal range.

[polldaddy:9971376]

 

Continue to: The authors' observations

 

 

The authors’ observations

Several factors may contribute to an increased chance of misdiagnosis of a psychiatric illness, especially when evaluating children. Compared with adults, children have a limited ability to explain their symptoms, and given their limited cognitive capacity, they may have difficulty identifying their symptoms as functionally limiting. A comprehensive clinical evaluation, including detailed interviews with the patient, the patient’s parents, and if possible, the patient’s teachers, is required to assess the child’s symptomatology and make an accurate clinical diagnosis.

On closer sequential evaluations with M and his family, we determined that the “voices” he was hearing were actually intrusive thoughts, and not hallucinations. M clarified this by saying that first he feels a “pressure”-like sensation in his head, followed by repeated intrusive thoughts of voiding his bladder that compel him to go to the restroom to try to urinate. He feels temporary relief after complying with the urge, even when he passes only a small amount of urine or just washes his hands. After a brief period of relief, this process repeats itself. Further, he was able to clarify his experience while eating food, where he first felt a “pressure”-like sensation in his head, followed by intrusive thoughts of choking that result in him not eating.

This led us to a more appropriate diagnosis of OCD (Table 11). The incidence of OCD has 2 peaks, with different gender distributions. The first peak occurs in childhood, with symptoms mostly arising between 7 and 12 years of age and affecting boys more often than girls. The second peak occurs in early adulthood, at a mean age of 21 years, with a slight female majority.2 However, OCD is often under recognized and undertreated, perhaps due to its extensive heterogeneity; symptom presentations and comorbidity patterns can vary noticeably between individual patients as well as age groups.

 

OCD is characterized by the presence of obsessions or compulsions that wax and wane in severity, are time-consuming (at least 1 hour per day), and cause subjective distress or interfere with life of the patient or the family. Adults with OCD recognize at some level that the obsessions and/or compulsions are excessive and unreasonable, although children are not required to have this insight to meet criteria for the diagnosis.1 Rating scales, such as the Children’s Yale-Brown Obsessive-Compulsive Scale, Dimensional Yale-Brown Obsessive-Compulsive Scale, and Family Accommodation Scale, are useful to obtain detailed information regarding OCD symptoms, tics, and other factors relevant to the diagnosis.

Continue to: M's symptomatology...

 

 

M’s symptomatology did not appear to be psychotic. He was screened for positive or negative symptoms of psychosis, which he and his family clearly denied. Moreover, M’s compulsions (going to the restroom) were typically performed in response to his obsessions (urge to void his bladder) to reduce his distress, which is different from schizophrenia, in which repetitive behaviors are performed in response to psychotic ideation, and not obsessions (Table 23-5).

M’s inattentiveness in the classroom was found to be related to his obsessions and compulsions, and not part of a symptom cluster characterizing ADHD. Teachers often interpret inattention and poor classroom performance as ADHD, but having detailed conversations with teachers often is helpful in understanding the nature of a child’s symptomology and making the appropriate diagnosis.

 

Establishing the correct clinical diagnosis is critical because it is the starting point in treatment. First-line medication for one condition may exacerbate the symptoms of others. For example, in addition to having a large adverse-effect burden, antipsychotics can induce de novo obsessive–compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors (SSRIs) may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.6 Similarly, stimulant medications for ADHD may exacerbate OCS and may even induce them on their own.7,8

[polldaddy:9971377]

 

Continue to: The authors' observations

 

 

The authors’ observations

Studies have reported an average of 2.5 years from the onset of OCD symptoms to diagnosis in the United States.9 A key reason for this delay, which is more frequently encountered in pediatric patients, is secrecy. Children often feel embarrassed about their symptoms and conceal them until the interference with their functioning becomes extremely disabling. In some cases, symptoms may closely resemble normal childhood routines. In fact, some repetitive behaviors may be normal in some developmental stages, and OCD could be conceptualized as a pathological condition with continuity of normal behaviors during different developmental periods.10

 

Also, symptoms may go unnoticed for quite some time as unsuspecting and well-intentioned parents and family members become overly involved in the child’s rituals (eg, allowing for increasing frequent prolonged bathroom breaks or frequent change of clothing, etc.). This well-established phenomenon, termed accommodation, is defined as participation of family members in a child’s OCD–related rituals.11 Especially when symptoms are mild or the child is functioning well, accommodation can make it difficult for parents to realize the presence or nature of a problem, as they might tend to minimize their child’s symptoms as representing a unique personality trait or a special “quirk.” Parents generally will seek treatment when their child’s symptoms become more impairing and begin to interfere with social functioning, school performance, or family functioning.

The clinical picture is further complicated by comorbidity. Approximately 60% to 80% of children and adolescents with OCD have ≥1 comorbid psychiatric disorders. Some of the most common include tic disorders, ADHD, anxiety disorders, and mood or eating disorders.9

[polldaddy:9971379]

 

Continue to: TREATMENT Combination therapy

 

 

TREATMENT Combination therapy

In keeping with American Academy of Child and Adolescent Psychiatry guidelines on treating OCD (Table 312), we start M on fluoxetine 10 mg/d. He also begins CBT. Fluoxetine is slowly titrated to 40 mg/d while M engages in learning and utilizing CBT techniques to manage his OCD.

The authors’ observations

The combination of CBT and medication has been suggested as the treatment of choice for moderate and severe OCD.12 The Pediatric OCD Treatment Study, a 5-year, 3-site outcome study designed to compare placebo, sertraline, CBT, and combined CBT and sertraline, concluded that the combined treatment (CBT plus sertraline) was more effective than CBT alone or sertraline alone.13 The effect sizes for the combined treatment, CBT alone, and sertraline alone were 1.4, 0.97, and 0.67, respectively. Remission rates for SSRIs alone are <33%.13,14

SSRIs are the first-line medication for OCD in children, adolescents, and adults (Table 312). Well-designed clinical trials have demonstrated the efficacy and safety of the SSRIs fluoxetine, sertraline, and fluvoxamine (alone or combined with CBT) in children and adolescents with OCD.13 Other SSRIs, such as citalopram, paroxetine, and escitalopram, also have demonstrated efficacy in children and adolescents with OCD, even though the FDA has not yet approved their use in pediatric patients.12 Despite a positive trial of paroxetine in pediatric OCD,12 there have been concerns related to its higher rates of treatment-emergent suicidality,15 lower likelihood of treatment response,16 and its particularly short half-life in pediatric patients.17

Clomipramine is a tricyclic antidepressant with serotonergic properties that is used alone or to boost the effect of an SSRI when there is a partial response. It should be introduced at a low dose in pediatric patients (before age 12) and closely monitored for anticholinergic and cardiac adverse effects. A systemic review and meta-analysis of early treatment responses of SSRIs and clomipramine in pediatric OCD indicated that the greatest benefits occurred early in treatment.18 Clomipramine was associated with a greater measured benefit compared with placebo than SSRIs; there was no evidence of a relationship between SSRI dosing and treatment effect, although data were limited. Adults and children with OCD demonstrated a similar degree and time course of response to SSRIs in OCD.18

Treatment should start with a low dose to reduce the risk of adverse effects with an adequate trial for 10 to 16 weeks at adequate doses. Most experts suggest that treatment should continue for at least 12 months after symptom resolution or stabilization, followed by a very gradual cessation.19

Continue to: OUTCOME Improvement in functioning

 

 

OUTCOME Improvement in functioning

After 12 months of combined CBT and fluoxetine, M’s global assessment of functioning (GAF) scale score improves from 35 to 80, indicating major improvement in overall functional level.

Acknowledgement

The authors thank Uzoma Osuchukwu, MD, ex-fellow, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York, for his assistance with this article.

 

 

Bottom Line

Obsessive-compulsive disorder may masquerade as a schizophrenia spectrum disorder, particularly in younger patients. Accurate differentiation is crucial because antipsychotics can induce de novo obsessive-compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.

Related Resource

  • Raveendranathan D, Shiva L, Sharma E, et al. Obsessive compulsive disorder masquerading as psychosis. Indian J Psychol Med. 2012;34(2):179-180.  

Drug Brand Names

Citalopram Celexa
Clomipramine Anafranil
Escitalopram Lexapro
Fluoxetine Prozac
Fluvoxamine Luvox
Paroxetine Paxil
Sertraline Zoloft

CASE Auditory hallucinations?

M, age 10, has had multiple visits to the pediatric emergency department (PED) with the chief concern of excessive urinary frequency. At each visit, the medical workup has been negative and he was discharged home. After a few months, M’s parents bring their son back to the PED because he reports hearing “voices in my head” and “feeling tense and scared.” When these feelings become too overwhelming, M stops eating and experiences substantial fear and anxiety that require his mother’s repeated reassurances. M’s mother reports that 2 weeks before his most recent PED visit, he became increasingly anxious and disturbed, and said he was afraid most of the time, and worried about the safety of his family for no apparent reason.

The psychiatrist evaluates M in the PED and diagnoses him with unspecified schizophrenia spectrum and other psychotic disorder based on his persistent report of auditory and tactile hallucinations, including hearing a voice of a man telling him he was going to choke on his food and feeling someone touch his arm to soothe him during his anxious moments. M does not meet criteria for acute inpatient hospitalization, and is discharged home with referral to follow-up at our child and adolescent psychiatry outpatient clinic.

On subsequent evaluation in our clinic, M reports most of the same about his experience hearing “voices in my head” that repeatedly suggest “I might choke on my food and end up seriously ill in the hospital.” He started to hear the “voices” after he witnessed his sister choke while eating a few days earlier. He also mentions that the “voices” tell him “you have to use the restroom.” As a result, he uses the restroom several times before leaving for home and is frequently late for school. His parents accommodate his behavior—his mother allows him to use the bathroom multiple times, and his father overlooks the behavior as part of school anxiety.

At school, his teacher reports a concern for attention-deficit/hyperactivity disorder (ADHD) based on M’s continuous inattentiveness in class and dropping grades. He asks for bathroom breaks up to 15 times a day, which disrupts his class work.

These behaviors have led to a gradual 1-year decline in his overall functioning, including difficulty at school for requesting too many bathroom breaks; having to repeat the 3rd grade; and incurring multiple hospital visits for evaluation of his various complaints. M has become socially isolated and withdrawn from friends and family.

M’s developmental history is normal and his family history is negative for any psychiatric disorder. Medical history and physical examination are unremarkable. CT scan of his head is unremarkable, and all hematologic and biochemistry laboratory test values are within normal range.

[polldaddy:9971376]

 

Continue to: The authors' observations

 

 

The authors’ observations

Several factors may contribute to an increased chance of misdiagnosis of a psychiatric illness, especially when evaluating children. Compared with adults, children have a limited ability to explain their symptoms, and given their limited cognitive capacity, they may have difficulty identifying their symptoms as functionally limiting. A comprehensive clinical evaluation, including detailed interviews with the patient, the patient’s parents, and if possible, the patient’s teachers, is required to assess the child’s symptomatology and make an accurate clinical diagnosis.

On closer sequential evaluations with M and his family, we determined that the “voices” he was hearing were actually intrusive thoughts, and not hallucinations. M clarified this by saying that first he feels a “pressure”-like sensation in his head, followed by repeated intrusive thoughts of voiding his bladder that compel him to go to the restroom to try to urinate. He feels temporary relief after complying with the urge, even when he passes only a small amount of urine or just washes his hands. After a brief period of relief, this process repeats itself. Further, he was able to clarify his experience while eating food, where he first felt a “pressure”-like sensation in his head, followed by intrusive thoughts of choking that result in him not eating.

This led us to a more appropriate diagnosis of OCD (Table 11). The incidence of OCD has 2 peaks, with different gender distributions. The first peak occurs in childhood, with symptoms mostly arising between 7 and 12 years of age and affecting boys more often than girls. The second peak occurs in early adulthood, at a mean age of 21 years, with a slight female majority.2 However, OCD is often under recognized and undertreated, perhaps due to its extensive heterogeneity; symptom presentations and comorbidity patterns can vary noticeably between individual patients as well as age groups.

 

OCD is characterized by the presence of obsessions or compulsions that wax and wane in severity, are time-consuming (at least 1 hour per day), and cause subjective distress or interfere with life of the patient or the family. Adults with OCD recognize at some level that the obsessions and/or compulsions are excessive and unreasonable, although children are not required to have this insight to meet criteria for the diagnosis.1 Rating scales, such as the Children’s Yale-Brown Obsessive-Compulsive Scale, Dimensional Yale-Brown Obsessive-Compulsive Scale, and Family Accommodation Scale, are useful to obtain detailed information regarding OCD symptoms, tics, and other factors relevant to the diagnosis.

Continue to: M's symptomatology...

 

 

M’s symptomatology did not appear to be psychotic. He was screened for positive or negative symptoms of psychosis, which he and his family clearly denied. Moreover, M’s compulsions (going to the restroom) were typically performed in response to his obsessions (urge to void his bladder) to reduce his distress, which is different from schizophrenia, in which repetitive behaviors are performed in response to psychotic ideation, and not obsessions (Table 23-5).

M’s inattentiveness in the classroom was found to be related to his obsessions and compulsions, and not part of a symptom cluster characterizing ADHD. Teachers often interpret inattention and poor classroom performance as ADHD, but having detailed conversations with teachers often is helpful in understanding the nature of a child’s symptomology and making the appropriate diagnosis.

 

Establishing the correct clinical diagnosis is critical because it is the starting point in treatment. First-line medication for one condition may exacerbate the symptoms of others. For example, in addition to having a large adverse-effect burden, antipsychotics can induce de novo obsessive–compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors (SSRIs) may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.6 Similarly, stimulant medications for ADHD may exacerbate OCS and may even induce them on their own.7,8

[polldaddy:9971377]

 

Continue to: The authors' observations

 

 

The authors’ observations

Studies have reported an average of 2.5 years from the onset of OCD symptoms to diagnosis in the United States.9 A key reason for this delay, which is more frequently encountered in pediatric patients, is secrecy. Children often feel embarrassed about their symptoms and conceal them until the interference with their functioning becomes extremely disabling. In some cases, symptoms may closely resemble normal childhood routines. In fact, some repetitive behaviors may be normal in some developmental stages, and OCD could be conceptualized as a pathological condition with continuity of normal behaviors during different developmental periods.10

 

Also, symptoms may go unnoticed for quite some time as unsuspecting and well-intentioned parents and family members become overly involved in the child’s rituals (eg, allowing for increasing frequent prolonged bathroom breaks or frequent change of clothing, etc.). This well-established phenomenon, termed accommodation, is defined as participation of family members in a child’s OCD–related rituals.11 Especially when symptoms are mild or the child is functioning well, accommodation can make it difficult for parents to realize the presence or nature of a problem, as they might tend to minimize their child’s symptoms as representing a unique personality trait or a special “quirk.” Parents generally will seek treatment when their child’s symptoms become more impairing and begin to interfere with social functioning, school performance, or family functioning.

The clinical picture is further complicated by comorbidity. Approximately 60% to 80% of children and adolescents with OCD have ≥1 comorbid psychiatric disorders. Some of the most common include tic disorders, ADHD, anxiety disorders, and mood or eating disorders.9

[polldaddy:9971379]

 

Continue to: TREATMENT Combination therapy

 

 

TREATMENT Combination therapy

In keeping with American Academy of Child and Adolescent Psychiatry guidelines on treating OCD (Table 312), we start M on fluoxetine 10 mg/d. He also begins CBT. Fluoxetine is slowly titrated to 40 mg/d while M engages in learning and utilizing CBT techniques to manage his OCD.

The authors’ observations

The combination of CBT and medication has been suggested as the treatment of choice for moderate and severe OCD.12 The Pediatric OCD Treatment Study, a 5-year, 3-site outcome study designed to compare placebo, sertraline, CBT, and combined CBT and sertraline, concluded that the combined treatment (CBT plus sertraline) was more effective than CBT alone or sertraline alone.13 The effect sizes for the combined treatment, CBT alone, and sertraline alone were 1.4, 0.97, and 0.67, respectively. Remission rates for SSRIs alone are <33%.13,14

SSRIs are the first-line medication for OCD in children, adolescents, and adults (Table 312). Well-designed clinical trials have demonstrated the efficacy and safety of the SSRIs fluoxetine, sertraline, and fluvoxamine (alone or combined with CBT) in children and adolescents with OCD.13 Other SSRIs, such as citalopram, paroxetine, and escitalopram, also have demonstrated efficacy in children and adolescents with OCD, even though the FDA has not yet approved their use in pediatric patients.12 Despite a positive trial of paroxetine in pediatric OCD,12 there have been concerns related to its higher rates of treatment-emergent suicidality,15 lower likelihood of treatment response,16 and its particularly short half-life in pediatric patients.17

Clomipramine is a tricyclic antidepressant with serotonergic properties that is used alone or to boost the effect of an SSRI when there is a partial response. It should be introduced at a low dose in pediatric patients (before age 12) and closely monitored for anticholinergic and cardiac adverse effects. A systemic review and meta-analysis of early treatment responses of SSRIs and clomipramine in pediatric OCD indicated that the greatest benefits occurred early in treatment.18 Clomipramine was associated with a greater measured benefit compared with placebo than SSRIs; there was no evidence of a relationship between SSRI dosing and treatment effect, although data were limited. Adults and children with OCD demonstrated a similar degree and time course of response to SSRIs in OCD.18

Treatment should start with a low dose to reduce the risk of adverse effects with an adequate trial for 10 to 16 weeks at adequate doses. Most experts suggest that treatment should continue for at least 12 months after symptom resolution or stabilization, followed by a very gradual cessation.19

Continue to: OUTCOME Improvement in functioning

 

 

OUTCOME Improvement in functioning

After 12 months of combined CBT and fluoxetine, M’s global assessment of functioning (GAF) scale score improves from 35 to 80, indicating major improvement in overall functional level.

Acknowledgement

The authors thank Uzoma Osuchukwu, MD, ex-fellow, Department of Child and Adolescent Psychiatry, Columbia University College of Physicians and Surgeons, Harlem Hospital Center, New York, New York, for his assistance with this article.

 

 

Bottom Line

Obsessive-compulsive disorder may masquerade as a schizophrenia spectrum disorder, particularly in younger patients. Accurate differentiation is crucial because antipsychotics can induce de novo obsessive-compulsive symptoms (OCS) or exacerbate preexisting OCS, and selective serotonin reuptake inhibitors may exacerbate psychosis in schizo-obsessive patients with a history of impulsivity and aggressiveness.

Related Resource

  • Raveendranathan D, Shiva L, Sharma E, et al. Obsessive compulsive disorder masquerading as psychosis. Indian J Psychol Med. 2012;34(2):179-180.  

Drug Brand Names

Citalopram Celexa
Clomipramine Anafranil
Escitalopram Lexapro
Fluoxetine Prozac
Fluvoxamine Luvox
Paroxetine Paxil
Sertraline Zoloft

References

1. Diagnostic and statistical manual of mental disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.
2. Geller D, Biederman J, Jones J, et al. Is juvenile obsessive-compulsive disorder a developmental subtype of the disorder? A review of the pediatric literature. J Am Acad Child Adolesc Psychiatry.1998;37(4):420-427.
3. Huppert JD, Simpson HB, Nissenson KJ, et al. Quality of life and functional impairment in obsessive-compulsive disorder: A comparison of patients with and without comorbidity, patients in remission, and healthy controls. Depress Anxiety. 2009;26(1):39-45.
4. Sobel W, Wolski R, Cancro R, et al. Interpersonal relatedness and paranoid schizophrenia. Am J Psychiatry.1996;153(8):1084-1087.
5. Meares A. The diagnosis of prepsychotic schizophrenia. Lancet. 1959;1(7063):55-58.
6. Poyurovsky M, Weizman A, Weizman R. Obsessive-compulsive disorder in schizophrenia: Clinical characteristics and treatment. CNS Drugs. 2004;18(14):989-1010.
7. Kouris S. Methylphenidate-induced obsessive-compulsiveness. J Am Acad Child Adolesc Psychiatry. 1998;37(2):135.
8. Woolley JB, Heyman I. Dexamphetamine for obsessive-compulsive disorder. Am J Psychiatry. 2003;160(1):183.
9. Geller DA. Obsessive-compulsive and spectrum disorders in children and adolescents. Psychiatr Clin N Am. 2006;29(2):352-370.
10. Evans DW, Milanak ME, Medeiros B, et al. Magical beliefs and rituals in young children. Child Psychiatry Hum Dev. 2002;33(1):43-58.
11. Amir N, Freshman M, Foa E. Family distress and involvement in relatives of obsessive-compulsive disorder patients. J Anxiety Disord. 2000;14(3):209-217.
12. Practice parameter for the assessment and treatment of children and adolescents with obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2012;51(1):98-113.
13. Pediatric OCD Treatment Study (POTS) Team. Cognitive-behavior therapy, sertraline, and their combination for children and adolescents with obsessive-compulsive disorder: The Pediatric OCD Treatment Study (POTS) randomized controlled trial. JAMA. 2004;292(16):1969-1976.
14. Franklin ME, Sapyta J, Freeman JB, et al. Cognitive behavior therapy augmentation of pharmacotherapy in pediatric obsessive-compulsive disorder: The Pediatric OCD Treatment Study II (POTS II) randomized controlled trial. JAMA. 2011;306(11):1224-1232.
15. Wagner KD, Asarnow JR, Vitiello B, et al. Out of the black box: treatment of resistant depression in adolescents and the antidepressant controversy. J Child Adolesc Psychopharmacol. 2012;22(1):5-10.
16. Sakolsky DJ, Perel JM, Emslie GJ, et al. Antidepressant exposure as a predictor of clinical outcomes in the treatment of resistant depression in adolescents (TORDIA) study. J Clin Psychopharmacol. 2011;31(1):92-97.
17. Findling RL. How (not) to dose antidepressants and antipsychotics for children. Current Psychiatry. 2007;6(6):79-83.
18. Varigonda AL, Jakubovski E, Bloch MH. Systematic review and meta-analysis: early treatment responses of selective serotonin reuptake inhibitors and clomipramine in pediatric obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2016 Oct;55(10):851-859.e2.
19. Mancuso E, Faro A, Joshi G, et al. Treatment of pediatric obsessive-compulsive disorder: a review. J Child Adolesc Psychopharmacol. 2010;20(4):299-308.

References

1. Diagnostic and statistical manual of mental disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.
2. Geller D, Biederman J, Jones J, et al. Is juvenile obsessive-compulsive disorder a developmental subtype of the disorder? A review of the pediatric literature. J Am Acad Child Adolesc Psychiatry.1998;37(4):420-427.
3. Huppert JD, Simpson HB, Nissenson KJ, et al. Quality of life and functional impairment in obsessive-compulsive disorder: A comparison of patients with and without comorbidity, patients in remission, and healthy controls. Depress Anxiety. 2009;26(1):39-45.
4. Sobel W, Wolski R, Cancro R, et al. Interpersonal relatedness and paranoid schizophrenia. Am J Psychiatry.1996;153(8):1084-1087.
5. Meares A. The diagnosis of prepsychotic schizophrenia. Lancet. 1959;1(7063):55-58.
6. Poyurovsky M, Weizman A, Weizman R. Obsessive-compulsive disorder in schizophrenia: Clinical characteristics and treatment. CNS Drugs. 2004;18(14):989-1010.
7. Kouris S. Methylphenidate-induced obsessive-compulsiveness. J Am Acad Child Adolesc Psychiatry. 1998;37(2):135.
8. Woolley JB, Heyman I. Dexamphetamine for obsessive-compulsive disorder. Am J Psychiatry. 2003;160(1):183.
9. Geller DA. Obsessive-compulsive and spectrum disorders in children and adolescents. Psychiatr Clin N Am. 2006;29(2):352-370.
10. Evans DW, Milanak ME, Medeiros B, et al. Magical beliefs and rituals in young children. Child Psychiatry Hum Dev. 2002;33(1):43-58.
11. Amir N, Freshman M, Foa E. Family distress and involvement in relatives of obsessive-compulsive disorder patients. J Anxiety Disord. 2000;14(3):209-217.
12. Practice parameter for the assessment and treatment of children and adolescents with obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2012;51(1):98-113.
13. Pediatric OCD Treatment Study (POTS) Team. Cognitive-behavior therapy, sertraline, and their combination for children and adolescents with obsessive-compulsive disorder: The Pediatric OCD Treatment Study (POTS) randomized controlled trial. JAMA. 2004;292(16):1969-1976.
14. Franklin ME, Sapyta J, Freeman JB, et al. Cognitive behavior therapy augmentation of pharmacotherapy in pediatric obsessive-compulsive disorder: The Pediatric OCD Treatment Study II (POTS II) randomized controlled trial. JAMA. 2011;306(11):1224-1232.
15. Wagner KD, Asarnow JR, Vitiello B, et al. Out of the black box: treatment of resistant depression in adolescents and the antidepressant controversy. J Child Adolesc Psychopharmacol. 2012;22(1):5-10.
16. Sakolsky DJ, Perel JM, Emslie GJ, et al. Antidepressant exposure as a predictor of clinical outcomes in the treatment of resistant depression in adolescents (TORDIA) study. J Clin Psychopharmacol. 2011;31(1):92-97.
17. Findling RL. How (not) to dose antidepressants and antipsychotics for children. Current Psychiatry. 2007;6(6):79-83.
18. Varigonda AL, Jakubovski E, Bloch MH. Systematic review and meta-analysis: early treatment responses of selective serotonin reuptake inhibitors and clomipramine in pediatric obsessive-compulsive disorder. J Am Acad Child Adolesc Psychiatry. 2016 Oct;55(10):851-859.e2.
19. Mancuso E, Faro A, Joshi G, et al. Treatment of pediatric obsessive-compulsive disorder: a review. J Child Adolesc Psychopharmacol. 2010;20(4):299-308.

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Psychiatric consults: Documenting 6 essential elements

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Psychiatric consults: Documenting 6 essential elements

Written communication is an essential skill for a consultation-liaison (C-L) psychiatrist, but unfortunately, how to write a consultation note is not part of formal didactics in medical school or residency training.1 Documentation of a consultation note is a permanent medical record entry that conveys current physician-to-physician information. While considerable literature describes the consultation process, little has been published about composing a consultation note.1,2 Residents and clinicians who do not have frequent consultations may be unfamiliar with the consultation environment and their role as an expert consultant. Therefore, more explicit guidance on documentation and optimal formatting of the consultation note is needed.

The Box provides an outline for completing the Recommendations/Treatment Plan section of psychiatric consultation notes. When providing your recommendations, it is best to use bullet points, numbering, or bold text; do not bury the information in a dense paragraph.3 Be sure to address each of the following 6 elements.

1. Primary consult concern. The first section of the Recommendations section should include the reason for the consult, which may be the most important part of the consultation process.1,2 It is important to recognize that an unclear consult question may be a sign of the primary team’s knowledge gap in psychiatry. The role of the C-L psychiatrist is to help the primary team organize their thoughts and concerns regarding their patient to decide on the final consult question.1 The active consult question may change as clinical issues evolve.

2. Safety and critical issues. Include an assessment of or recommendation on safety and critical issues. An important consideration is whether to recommend a patient sitter and to provide a reason for this recommendation. Occasionally, critical issues are more pressing than the primary consult concern. For example, there are several situations in which abnormal laboratory values and acute medical issues manifest as psychiatric symptoms, including hyponatremia, hypoglycemia, hypotension, low oxygen saturation, or infection. The connection between the 2 may not be clear to the primary treatment team; thus, include a statement to draw their attention to this.

3. Nonpharmacologic recommendations. To provide comprehensive care, consider all treatment modalities, and consider recruiting additional clinical disciplines, as appropriate. Patients may have complex medical and psychiatric presentations that are difficult to differentiate; therefore, C-L psychiatrists should not hesitate to recommend consults from other medical specialists as needed. Likewise, dealing with psychiatric concerns often is difficult for clinicians in other specialties. When possible, it may be helpful to provide brief recommendations about how to approach the patient to diffuse negative emotions and reactions among the treatment team.

4. Psychopharmacology. In this section, the C-L psychiatrist should provide information on the use of any psychotropic medications and an explanation of their indications. If there are discrepancies between a patient’s home and hospital-ordered medications, clarify which medications the patient should be taking while hospitalized. If the C-L treatment team recommends initiating a new medication, provide details regarding the specific medication, dose, route, administration time, and titration schedule, as well as the specific situation for any as-needed medications. It is important to include the indication for any recommended medications, as well as any potential adverse effects. If psychotropic medications are not indicated, add a statement to emphasize this.

5. Social work support. Document any issues that need to be clarified by social work. This might include clarification of a patient’s insurance coverage, current living situation, or durable power of attorney. Also, document how the treatment team would prefer social work to assist with the patient’s care by (for example) providing the patient with resources for outpatient mental health and/or substance abuse treatment or housing options.

Continue to: Disposition

 

 

6. Disposition. Finally, include a recommendation regarding disposition. If transfer to a psychiatric facility is not indicated, provide a statement to affirm this. If transfer to a psychiatric facility is recommended, include a discussion of the patient’s appropriateness in the assessment and recommendations. It is helpful to inform the primary team of criteria that may or may not allow the patient to transfer to or be accepted by a psychiatry unit (eg, the patient will need to be off IV medications and able to tolerate oral intake prior to transfer). When transfer is not possible, communicate the reason to the primary treatment team and other ancillary staff.

Communicating responsibilities and expectations

After concluding the Recommendations section, end the consultation note with a brief sentence of gratitude (eg, “Thank you for this consultation and allowing us to assist in the care of your patient.”) and a comment regarding the C-L treatment team’s plan for follow-up. Also, include your contact information in case the primary treatment team has any questions or concerns.

The Recommendations section of a psychiatric consultation note is vital to convey current physician-to-physician recommendations. With the potential complexities in assessing and caring for a medically ill patient with comorbid psychiatric diagnoses, psychiatrists with less C-L experience may be unfamiliar with the essential elements of a consultation note. It is helpful to use a Template to ensure that the consultation and documentation are complete.

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References

1. Garrick TR, Stotland, NL. How to write a psychiatric consultation. Am J Psychiatry. 1982;139(7):849-855.
2. Alexander T, Bloch S. The written report in consultation-liaison psychiatry: a proposed schema. Aust N Z J Psychiatry. 2002;36(2):251-258.
3. von Gunten CF, Weissman DE. Writing the consultation note #267. J Palliat Med. 2013;16(5):579-580.

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Dr. Meyer Karre is Assistant Professor, and Dr. Gih is Associate Professor, Department of Psychiatry, the University of Nebraska Medical Center, Omaha, Nebraska.

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Author and Disclosure Information

Dr. Meyer Karre is Assistant Professor, and Dr. Gih is Associate Professor, Department of Psychiatry, the University of Nebraska Medical Center, Omaha, Nebraska.

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Article PDF
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Written communication is an essential skill for a consultation-liaison (C-L) psychiatrist, but unfortunately, how to write a consultation note is not part of formal didactics in medical school or residency training.1 Documentation of a consultation note is a permanent medical record entry that conveys current physician-to-physician information. While considerable literature describes the consultation process, little has been published about composing a consultation note.1,2 Residents and clinicians who do not have frequent consultations may be unfamiliar with the consultation environment and their role as an expert consultant. Therefore, more explicit guidance on documentation and optimal formatting of the consultation note is needed.

The Box provides an outline for completing the Recommendations/Treatment Plan section of psychiatric consultation notes. When providing your recommendations, it is best to use bullet points, numbering, or bold text; do not bury the information in a dense paragraph.3 Be sure to address each of the following 6 elements.

1. Primary consult concern. The first section of the Recommendations section should include the reason for the consult, which may be the most important part of the consultation process.1,2 It is important to recognize that an unclear consult question may be a sign of the primary team’s knowledge gap in psychiatry. The role of the C-L psychiatrist is to help the primary team organize their thoughts and concerns regarding their patient to decide on the final consult question.1 The active consult question may change as clinical issues evolve.

2. Safety and critical issues. Include an assessment of or recommendation on safety and critical issues. An important consideration is whether to recommend a patient sitter and to provide a reason for this recommendation. Occasionally, critical issues are more pressing than the primary consult concern. For example, there are several situations in which abnormal laboratory values and acute medical issues manifest as psychiatric symptoms, including hyponatremia, hypoglycemia, hypotension, low oxygen saturation, or infection. The connection between the 2 may not be clear to the primary treatment team; thus, include a statement to draw their attention to this.

3. Nonpharmacologic recommendations. To provide comprehensive care, consider all treatment modalities, and consider recruiting additional clinical disciplines, as appropriate. Patients may have complex medical and psychiatric presentations that are difficult to differentiate; therefore, C-L psychiatrists should not hesitate to recommend consults from other medical specialists as needed. Likewise, dealing with psychiatric concerns often is difficult for clinicians in other specialties. When possible, it may be helpful to provide brief recommendations about how to approach the patient to diffuse negative emotions and reactions among the treatment team.

4. Psychopharmacology. In this section, the C-L psychiatrist should provide information on the use of any psychotropic medications and an explanation of their indications. If there are discrepancies between a patient’s home and hospital-ordered medications, clarify which medications the patient should be taking while hospitalized. If the C-L treatment team recommends initiating a new medication, provide details regarding the specific medication, dose, route, administration time, and titration schedule, as well as the specific situation for any as-needed medications. It is important to include the indication for any recommended medications, as well as any potential adverse effects. If psychotropic medications are not indicated, add a statement to emphasize this.

5. Social work support. Document any issues that need to be clarified by social work. This might include clarification of a patient’s insurance coverage, current living situation, or durable power of attorney. Also, document how the treatment team would prefer social work to assist with the patient’s care by (for example) providing the patient with resources for outpatient mental health and/or substance abuse treatment or housing options.

Continue to: Disposition

 

 

6. Disposition. Finally, include a recommendation regarding disposition. If transfer to a psychiatric facility is not indicated, provide a statement to affirm this. If transfer to a psychiatric facility is recommended, include a discussion of the patient’s appropriateness in the assessment and recommendations. It is helpful to inform the primary team of criteria that may or may not allow the patient to transfer to or be accepted by a psychiatry unit (eg, the patient will need to be off IV medications and able to tolerate oral intake prior to transfer). When transfer is not possible, communicate the reason to the primary treatment team and other ancillary staff.

Communicating responsibilities and expectations

After concluding the Recommendations section, end the consultation note with a brief sentence of gratitude (eg, “Thank you for this consultation and allowing us to assist in the care of your patient.”) and a comment regarding the C-L treatment team’s plan for follow-up. Also, include your contact information in case the primary treatment team has any questions or concerns.

The Recommendations section of a psychiatric consultation note is vital to convey current physician-to-physician recommendations. With the potential complexities in assessing and caring for a medically ill patient with comorbid psychiatric diagnoses, psychiatrists with less C-L experience may be unfamiliar with the essential elements of a consultation note. It is helpful to use a Template to ensure that the consultation and documentation are complete.

Written communication is an essential skill for a consultation-liaison (C-L) psychiatrist, but unfortunately, how to write a consultation note is not part of formal didactics in medical school or residency training.1 Documentation of a consultation note is a permanent medical record entry that conveys current physician-to-physician information. While considerable literature describes the consultation process, little has been published about composing a consultation note.1,2 Residents and clinicians who do not have frequent consultations may be unfamiliar with the consultation environment and their role as an expert consultant. Therefore, more explicit guidance on documentation and optimal formatting of the consultation note is needed.

The Box provides an outline for completing the Recommendations/Treatment Plan section of psychiatric consultation notes. When providing your recommendations, it is best to use bullet points, numbering, or bold text; do not bury the information in a dense paragraph.3 Be sure to address each of the following 6 elements.

1. Primary consult concern. The first section of the Recommendations section should include the reason for the consult, which may be the most important part of the consultation process.1,2 It is important to recognize that an unclear consult question may be a sign of the primary team’s knowledge gap in psychiatry. The role of the C-L psychiatrist is to help the primary team organize their thoughts and concerns regarding their patient to decide on the final consult question.1 The active consult question may change as clinical issues evolve.

2. Safety and critical issues. Include an assessment of or recommendation on safety and critical issues. An important consideration is whether to recommend a patient sitter and to provide a reason for this recommendation. Occasionally, critical issues are more pressing than the primary consult concern. For example, there are several situations in which abnormal laboratory values and acute medical issues manifest as psychiatric symptoms, including hyponatremia, hypoglycemia, hypotension, low oxygen saturation, or infection. The connection between the 2 may not be clear to the primary treatment team; thus, include a statement to draw their attention to this.

3. Nonpharmacologic recommendations. To provide comprehensive care, consider all treatment modalities, and consider recruiting additional clinical disciplines, as appropriate. Patients may have complex medical and psychiatric presentations that are difficult to differentiate; therefore, C-L psychiatrists should not hesitate to recommend consults from other medical specialists as needed. Likewise, dealing with psychiatric concerns often is difficult for clinicians in other specialties. When possible, it may be helpful to provide brief recommendations about how to approach the patient to diffuse negative emotions and reactions among the treatment team.

4. Psychopharmacology. In this section, the C-L psychiatrist should provide information on the use of any psychotropic medications and an explanation of their indications. If there are discrepancies between a patient’s home and hospital-ordered medications, clarify which medications the patient should be taking while hospitalized. If the C-L treatment team recommends initiating a new medication, provide details regarding the specific medication, dose, route, administration time, and titration schedule, as well as the specific situation for any as-needed medications. It is important to include the indication for any recommended medications, as well as any potential adverse effects. If psychotropic medications are not indicated, add a statement to emphasize this.

5. Social work support. Document any issues that need to be clarified by social work. This might include clarification of a patient’s insurance coverage, current living situation, or durable power of attorney. Also, document how the treatment team would prefer social work to assist with the patient’s care by (for example) providing the patient with resources for outpatient mental health and/or substance abuse treatment or housing options.

Continue to: Disposition

 

 

6. Disposition. Finally, include a recommendation regarding disposition. If transfer to a psychiatric facility is not indicated, provide a statement to affirm this. If transfer to a psychiatric facility is recommended, include a discussion of the patient’s appropriateness in the assessment and recommendations. It is helpful to inform the primary team of criteria that may or may not allow the patient to transfer to or be accepted by a psychiatry unit (eg, the patient will need to be off IV medications and able to tolerate oral intake prior to transfer). When transfer is not possible, communicate the reason to the primary treatment team and other ancillary staff.

Communicating responsibilities and expectations

After concluding the Recommendations section, end the consultation note with a brief sentence of gratitude (eg, “Thank you for this consultation and allowing us to assist in the care of your patient.”) and a comment regarding the C-L treatment team’s plan for follow-up. Also, include your contact information in case the primary treatment team has any questions or concerns.

The Recommendations section of a psychiatric consultation note is vital to convey current physician-to-physician recommendations. With the potential complexities in assessing and caring for a medically ill patient with comorbid psychiatric diagnoses, psychiatrists with less C-L experience may be unfamiliar with the essential elements of a consultation note. It is helpful to use a Template to ensure that the consultation and documentation are complete.

References

1. Garrick TR, Stotland, NL. How to write a psychiatric consultation. Am J Psychiatry. 1982;139(7):849-855.
2. Alexander T, Bloch S. The written report in consultation-liaison psychiatry: a proposed schema. Aust N Z J Psychiatry. 2002;36(2):251-258.
3. von Gunten CF, Weissman DE. Writing the consultation note #267. J Palliat Med. 2013;16(5):579-580.

References

1. Garrick TR, Stotland, NL. How to write a psychiatric consultation. Am J Psychiatry. 1982;139(7):849-855.
2. Alexander T, Bloch S. The written report in consultation-liaison psychiatry: a proposed schema. Aust N Z J Psychiatry. 2002;36(2):251-258.
3. von Gunten CF, Weissman DE. Writing the consultation note #267. J Palliat Med. 2013;16(5):579-580.

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Tardive dyskinesia: 5 Steps for prevention

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Tardive dyskinesia (TD) is an elusive-to-treat adverse effect of antipsychotics that has caused extreme discomfort (in a literal and figurative sense) for patients and their psychiatrists. In 2017, the prevalence of TD as a result of exposure to dopamine antagonists was approximately 30% with first-generation antipsychotics and 20% with second-generation antipsychotics.1 There have been several effective attempts at reducing rates of TD, including lowering the dosing, shifting to second-generation antipsychotics, and using recently introduced pharmacologic treatments for TD. The past 2 years have seen increased efforts at treating this often-irreversible adverse effect with pharmacotherapy, such as the recently marketed vesicular monoamine transporter-2 (VMAT2) inhibitors valbenazine and deutetrabenazine, as well as the supplement Ginkgo biloba,2 although issues with cost, adverse effects, or drug–drug interactions could limit the benefits of these agents.

Despite these strategies, one approach has been largely overlooked: prevention. Although it is included in many guidelines and literature reports, prevention has become less of a standard of practice and more of a cliché. Prevention is the key strategy for lowering the rate of TD, and it should be the assumed responsibility of each clinician in every prescription they write throughout the entire continuum of care. Here, we provide steps to take to help prevent TD, and what to consider when TD occurs.

1. Realize that we are all responsible for TD. We know TD exists, but we often feel that this adverse effect is not our fault. Avoid adapting a philosophy of “someone else caused it,” “they didn’t cause it yet,” or “it’s going to happen anyway.” We must remember that every unnecessary exposure to a dopamine antagonist increases the risk of TD, even if we don’t see the adverse effect firsthand.

2. Treat first-episode psychosis early and aggressively. Doing so may prevent chronicity of the illness, which would save a patient from long-term, high-dose exposure to antipsychotics. Lower the risk of TD with atypical antipsychotics and offer long-acting injectables when possible to improve medication adherence.

3. Treat both acute and chronic symptoms of psychosis throughout the continuum of care. The choice of medication and dose should be reevaluated at each interaction to enhance improvement of acute symptoms and to minimize chronic adverse effects. Always recognize the differences in aggressive treatment of an acute episode of psychosis vs maintenance treatment of baseline symptoms. Also, assess for TD by conducting abnormal involuntary movement scale (AIMS) examinations at baseline and at least biannually.

4. Use clozapine instead of 2 antipsychotics in chronic, refractory patients when possible. Clozapine is largely underutilized, despite continued evidence of its superiority in effectiveness and prevention of relapse3 vs other agents, and has a lower risk of TD. The use of polypharmacy, on the other hand, has continued to display a lack of added benefit in treating symptoms of psychosis, and an increase in adverse effects.4

5. Consider pharmacotherapy if TD has already occurred. Psychiatrists have been waiting for pharmacologic options for treating TD for quite some time. Explore using VMAT2 inhibitors and other agents when it is too late to implement prevention or when a patient’s symptoms are refractory to other treatments. However, avoid anticholinergic medications; there is insufficient data to support the use of these agents in the treatment of TD.5

References

1. Carbon M, Hsieh C, Kane J, et al. Tardive dyskinesia prevalence in the period of second-generation antipsychotic use: a meta-analysis. J Clin Psychiatry. 2017;78(3):e264-e278.
2. Zheng W, Xiang Y, Ng H, et al. Extract of ginkgo biloba for tardive dyskinesia: meta-analysis of randomized controlled trials. Pharmacopsychiatry. 2016;49(3):107-111.
3. Tiihonen J, Mittendorfer-Rutz E, Majak M, et al. Real-world effectiveness of antipsychotic treatments in a nationwide cohort of 29 823 patients with schizophrenia. JAMA Psychiatry. 2017;74(7):686-693.
4. Barnes TR, Paton C. Antipsychotic polypharmacy in schizophrenia: benefits and risks. CNS Drugs. 2011;25(5):383-399.
5. Bhidayasiri R, Fahn S, Weiner WJ, et al; American Academy of Neurology. Evidence-based guideline: treatment of tardive syndromes. Report of the Guideline Development Subcommittee of the American Academy of Neurology. Neurology. 2013;81(5):463-469.

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Tardive dyskinesia (TD) is an elusive-to-treat adverse effect of antipsychotics that has caused extreme discomfort (in a literal and figurative sense) for patients and their psychiatrists. In 2017, the prevalence of TD as a result of exposure to dopamine antagonists was approximately 30% with first-generation antipsychotics and 20% with second-generation antipsychotics.1 There have been several effective attempts at reducing rates of TD, including lowering the dosing, shifting to second-generation antipsychotics, and using recently introduced pharmacologic treatments for TD. The past 2 years have seen increased efforts at treating this often-irreversible adverse effect with pharmacotherapy, such as the recently marketed vesicular monoamine transporter-2 (VMAT2) inhibitors valbenazine and deutetrabenazine, as well as the supplement Ginkgo biloba,2 although issues with cost, adverse effects, or drug–drug interactions could limit the benefits of these agents.

Despite these strategies, one approach has been largely overlooked: prevention. Although it is included in many guidelines and literature reports, prevention has become less of a standard of practice and more of a cliché. Prevention is the key strategy for lowering the rate of TD, and it should be the assumed responsibility of each clinician in every prescription they write throughout the entire continuum of care. Here, we provide steps to take to help prevent TD, and what to consider when TD occurs.

1. Realize that we are all responsible for TD. We know TD exists, but we often feel that this adverse effect is not our fault. Avoid adapting a philosophy of “someone else caused it,” “they didn’t cause it yet,” or “it’s going to happen anyway.” We must remember that every unnecessary exposure to a dopamine antagonist increases the risk of TD, even if we don’t see the adverse effect firsthand.

2. Treat first-episode psychosis early and aggressively. Doing so may prevent chronicity of the illness, which would save a patient from long-term, high-dose exposure to antipsychotics. Lower the risk of TD with atypical antipsychotics and offer long-acting injectables when possible to improve medication adherence.

3. Treat both acute and chronic symptoms of psychosis throughout the continuum of care. The choice of medication and dose should be reevaluated at each interaction to enhance improvement of acute symptoms and to minimize chronic adverse effects. Always recognize the differences in aggressive treatment of an acute episode of psychosis vs maintenance treatment of baseline symptoms. Also, assess for TD by conducting abnormal involuntary movement scale (AIMS) examinations at baseline and at least biannually.

4. Use clozapine instead of 2 antipsychotics in chronic, refractory patients when possible. Clozapine is largely underutilized, despite continued evidence of its superiority in effectiveness and prevention of relapse3 vs other agents, and has a lower risk of TD. The use of polypharmacy, on the other hand, has continued to display a lack of added benefit in treating symptoms of psychosis, and an increase in adverse effects.4

5. Consider pharmacotherapy if TD has already occurred. Psychiatrists have been waiting for pharmacologic options for treating TD for quite some time. Explore using VMAT2 inhibitors and other agents when it is too late to implement prevention or when a patient’s symptoms are refractory to other treatments. However, avoid anticholinergic medications; there is insufficient data to support the use of these agents in the treatment of TD.5

Tardive dyskinesia (TD) is an elusive-to-treat adverse effect of antipsychotics that has caused extreme discomfort (in a literal and figurative sense) for patients and their psychiatrists. In 2017, the prevalence of TD as a result of exposure to dopamine antagonists was approximately 30% with first-generation antipsychotics and 20% with second-generation antipsychotics.1 There have been several effective attempts at reducing rates of TD, including lowering the dosing, shifting to second-generation antipsychotics, and using recently introduced pharmacologic treatments for TD. The past 2 years have seen increased efforts at treating this often-irreversible adverse effect with pharmacotherapy, such as the recently marketed vesicular monoamine transporter-2 (VMAT2) inhibitors valbenazine and deutetrabenazine, as well as the supplement Ginkgo biloba,2 although issues with cost, adverse effects, or drug–drug interactions could limit the benefits of these agents.

Despite these strategies, one approach has been largely overlooked: prevention. Although it is included in many guidelines and literature reports, prevention has become less of a standard of practice and more of a cliché. Prevention is the key strategy for lowering the rate of TD, and it should be the assumed responsibility of each clinician in every prescription they write throughout the entire continuum of care. Here, we provide steps to take to help prevent TD, and what to consider when TD occurs.

1. Realize that we are all responsible for TD. We know TD exists, but we often feel that this adverse effect is not our fault. Avoid adapting a philosophy of “someone else caused it,” “they didn’t cause it yet,” or “it’s going to happen anyway.” We must remember that every unnecessary exposure to a dopamine antagonist increases the risk of TD, even if we don’t see the adverse effect firsthand.

2. Treat first-episode psychosis early and aggressively. Doing so may prevent chronicity of the illness, which would save a patient from long-term, high-dose exposure to antipsychotics. Lower the risk of TD with atypical antipsychotics and offer long-acting injectables when possible to improve medication adherence.

3. Treat both acute and chronic symptoms of psychosis throughout the continuum of care. The choice of medication and dose should be reevaluated at each interaction to enhance improvement of acute symptoms and to minimize chronic adverse effects. Always recognize the differences in aggressive treatment of an acute episode of psychosis vs maintenance treatment of baseline symptoms. Also, assess for TD by conducting abnormal involuntary movement scale (AIMS) examinations at baseline and at least biannually.

4. Use clozapine instead of 2 antipsychotics in chronic, refractory patients when possible. Clozapine is largely underutilized, despite continued evidence of its superiority in effectiveness and prevention of relapse3 vs other agents, and has a lower risk of TD. The use of polypharmacy, on the other hand, has continued to display a lack of added benefit in treating symptoms of psychosis, and an increase in adverse effects.4

5. Consider pharmacotherapy if TD has already occurred. Psychiatrists have been waiting for pharmacologic options for treating TD for quite some time. Explore using VMAT2 inhibitors and other agents when it is too late to implement prevention or when a patient’s symptoms are refractory to other treatments. However, avoid anticholinergic medications; there is insufficient data to support the use of these agents in the treatment of TD.5

References

1. Carbon M, Hsieh C, Kane J, et al. Tardive dyskinesia prevalence in the period of second-generation antipsychotic use: a meta-analysis. J Clin Psychiatry. 2017;78(3):e264-e278.
2. Zheng W, Xiang Y, Ng H, et al. Extract of ginkgo biloba for tardive dyskinesia: meta-analysis of randomized controlled trials. Pharmacopsychiatry. 2016;49(3):107-111.
3. Tiihonen J, Mittendorfer-Rutz E, Majak M, et al. Real-world effectiveness of antipsychotic treatments in a nationwide cohort of 29 823 patients with schizophrenia. JAMA Psychiatry. 2017;74(7):686-693.
4. Barnes TR, Paton C. Antipsychotic polypharmacy in schizophrenia: benefits and risks. CNS Drugs. 2011;25(5):383-399.
5. Bhidayasiri R, Fahn S, Weiner WJ, et al; American Academy of Neurology. Evidence-based guideline: treatment of tardive syndromes. Report of the Guideline Development Subcommittee of the American Academy of Neurology. Neurology. 2013;81(5):463-469.

References

1. Carbon M, Hsieh C, Kane J, et al. Tardive dyskinesia prevalence in the period of second-generation antipsychotic use: a meta-analysis. J Clin Psychiatry. 2017;78(3):e264-e278.
2. Zheng W, Xiang Y, Ng H, et al. Extract of ginkgo biloba for tardive dyskinesia: meta-analysis of randomized controlled trials. Pharmacopsychiatry. 2016;49(3):107-111.
3. Tiihonen J, Mittendorfer-Rutz E, Majak M, et al. Real-world effectiveness of antipsychotic treatments in a nationwide cohort of 29 823 patients with schizophrenia. JAMA Psychiatry. 2017;74(7):686-693.
4. Barnes TR, Paton C. Antipsychotic polypharmacy in schizophrenia: benefits and risks. CNS Drugs. 2011;25(5):383-399.
5. Bhidayasiri R, Fahn S, Weiner WJ, et al; American Academy of Neurology. Evidence-based guideline: treatment of tardive syndromes. Report of the Guideline Development Subcommittee of the American Academy of Neurology. Neurology. 2013;81(5):463-469.

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Opioid Use Disorder: Challenges and Solutions to a Rising Epidemic

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    CME: Opioid Use Disorder: Challenges and Solutions to a Rising Epidemic

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        Depression risks identified in women

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        The risk of major depression was significantly higher in women of reproductive age if they had some type of government insurance or hypertension or if they smoked, according to an analysis of 3,705 nonpregnant women aged 20-44 years.

        The same group of women was significantly more likely to have minor depression, compared with those who were not depressed, if they had less than a high school education or asthma or if they smoked, reported Nan Guo, PhD, and her associates at Stanford (Calif.) University.

        The adjusted relative risk for major depression was a significant 2.49 for women if they had government, state, or military insurance, compared with the reference group – those who had private insurance. Women with no insurance had an adjusted RR of 1.84, which did not reach statistical significance, they said.

        The risk of major depression was also significantly higher for women with hypertension (RR, 2.09 vs. no hypertension) and for those who were current smokers (RR, 2.02), compared with never smokers. Former smokers had an RR of 0.86 vs. never smokers, but the difference was not significant, Dr. Guo and her associates said.

         

         

        Education was a major area of difference between women with minor depression and those with no depression. Compared with the reference group – college graduate or above – adjusted RRs for minor depression were 4.34 for those with less than a high school education, 2.92 for those with a high school education, and 2.59 for women with some college or an associate degree. Women with asthma were 2.11 times as likely to have minor depression as those without asthma, and current smokers had an RR of 1.66 for minor depression, compared with never smokers, the investigators said.

        The study was supported by funding from Stanford University. One investigator received an award from the National Institute of Child Health and Human Development. The investigators did not report any potential conflicts of interest.

        SOURCE: Obstet Gynecol. 2018 Apr;131(4):671-9.

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        The risk of major depression was significantly higher in women of reproductive age if they had some type of government insurance or hypertension or if they smoked, according to an analysis of 3,705 nonpregnant women aged 20-44 years.

        The same group of women was significantly more likely to have minor depression, compared with those who were not depressed, if they had less than a high school education or asthma or if they smoked, reported Nan Guo, PhD, and her associates at Stanford (Calif.) University.

        The adjusted relative risk for major depression was a significant 2.49 for women if they had government, state, or military insurance, compared with the reference group – those who had private insurance. Women with no insurance had an adjusted RR of 1.84, which did not reach statistical significance, they said.

        The risk of major depression was also significantly higher for women with hypertension (RR, 2.09 vs. no hypertension) and for those who were current smokers (RR, 2.02), compared with never smokers. Former smokers had an RR of 0.86 vs. never smokers, but the difference was not significant, Dr. Guo and her associates said.

         

         

        Education was a major area of difference between women with minor depression and those with no depression. Compared with the reference group – college graduate or above – adjusted RRs for minor depression were 4.34 for those with less than a high school education, 2.92 for those with a high school education, and 2.59 for women with some college or an associate degree. Women with asthma were 2.11 times as likely to have minor depression as those without asthma, and current smokers had an RR of 1.66 for minor depression, compared with never smokers, the investigators said.

        The study was supported by funding from Stanford University. One investigator received an award from the National Institute of Child Health and Human Development. The investigators did not report any potential conflicts of interest.

        SOURCE: Obstet Gynecol. 2018 Apr;131(4):671-9.

         

        The risk of major depression was significantly higher in women of reproductive age if they had some type of government insurance or hypertension or if they smoked, according to an analysis of 3,705 nonpregnant women aged 20-44 years.

        The same group of women was significantly more likely to have minor depression, compared with those who were not depressed, if they had less than a high school education or asthma or if they smoked, reported Nan Guo, PhD, and her associates at Stanford (Calif.) University.

        The adjusted relative risk for major depression was a significant 2.49 for women if they had government, state, or military insurance, compared with the reference group – those who had private insurance. Women with no insurance had an adjusted RR of 1.84, which did not reach statistical significance, they said.

        The risk of major depression was also significantly higher for women with hypertension (RR, 2.09 vs. no hypertension) and for those who were current smokers (RR, 2.02), compared with never smokers. Former smokers had an RR of 0.86 vs. never smokers, but the difference was not significant, Dr. Guo and her associates said.

         

         

        Education was a major area of difference between women with minor depression and those with no depression. Compared with the reference group – college graduate or above – adjusted RRs for minor depression were 4.34 for those with less than a high school education, 2.92 for those with a high school education, and 2.59 for women with some college or an associate degree. Women with asthma were 2.11 times as likely to have minor depression as those without asthma, and current smokers had an RR of 1.66 for minor depression, compared with never smokers, the investigators said.

        The study was supported by funding from Stanford University. One investigator received an award from the National Institute of Child Health and Human Development. The investigators did not report any potential conflicts of interest.

        SOURCE: Obstet Gynecol. 2018 Apr;131(4):671-9.

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        Managing schizophrenia as a chronic disease linked to better outcomes

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        – The secret to optimal long-term disease control in schizophrenia is to implement the same type of continuous and close management provided to other chronic diseases, like hypertension or inflammatory bowel disease, according to a lecture delivered at the annual meeting of the American College of Psychiatrists.

        In the Dean Award Lecture – a talk characterized as “a stroll through the long-term understanding of the treatment of schizophrenia” – Ira D. Glick, MD, said that, although antipsychotics provide the foundation of disease control, patients and families need to understand and respect disease chronicity.

        Dr. Ira D. Glick
        Dr. Glick remembered speculation in his training that bad parenting might be a cause or contributor to the development of schizophrenia. Now, genetic susceptibility is recognized as a dominant factor for both developing the disease and determining severity, said Dr. Glick, professor emeritus in the department of psychiatry and behavioral sciences at Stanford (Calif.) University. Regardless of etiology, however, he believes that convincing patients and families that schizophrenia is a lifetime disease is a critical first step to treatment compliance that optimizes adequate symptom control.

        “In the last 5 or 6 years, I did something that no one has ever done before. I looked at the outcomes of patients treated for decades,” Dr. Glick recounted. Specifically, he contacted patients who had been in his care for up to 50 years. In “this naturalistic study,” he specifically asked the patients to rate their adherence to antipsychotics and to provide a global assessment of their life satisfaction, both on a scale of 1-10.

         

         


        “What I found in a relatively large sample was that the more adherent patients were to their medication, the more likely they were to report adequate satisfaction with their life,” Dr. Glick said. For those who were not adherent, life in general “has been a disaster.”

        This finding is not entirely surprising given the power of antipsychotics to change thinking. However, for those engaged in the immediate task of controlling acute symptoms, the importance of chronicity might not be given adequate emphasis. This requires educating patients and their families about the need to embark on lifetime treatment, Dr. Glick said. Like a diagnosis of diabetes, a diagnosis of schizophrenia means constant vigilance for manifestations of disease and appropriate adjustments of therapy to improve long-term outcomes.

        Since evaluating the relationship between medication adherence and long-term outcomes in patients with schizophrenia treated at Stanford, the same type of evaluation was conducted with population samples from the Veterans Affairs system and from China. The data “show exactly the same thing,” Dr. Glick said.

        It is important to use every available resource in helping patients recognize and deal with schizophrenia chronicity. In addition to engaging families, he believes that organizations such as the National Alliance on Mental Illness or NAMI, are useful sources of support.

         

         

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        – The secret to optimal long-term disease control in schizophrenia is to implement the same type of continuous and close management provided to other chronic diseases, like hypertension or inflammatory bowel disease, according to a lecture delivered at the annual meeting of the American College of Psychiatrists.

        In the Dean Award Lecture – a talk characterized as “a stroll through the long-term understanding of the treatment of schizophrenia” – Ira D. Glick, MD, said that, although antipsychotics provide the foundation of disease control, patients and families need to understand and respect disease chronicity.

        Dr. Ira D. Glick
        Dr. Glick remembered speculation in his training that bad parenting might be a cause or contributor to the development of schizophrenia. Now, genetic susceptibility is recognized as a dominant factor for both developing the disease and determining severity, said Dr. Glick, professor emeritus in the department of psychiatry and behavioral sciences at Stanford (Calif.) University. Regardless of etiology, however, he believes that convincing patients and families that schizophrenia is a lifetime disease is a critical first step to treatment compliance that optimizes adequate symptom control.

        “In the last 5 or 6 years, I did something that no one has ever done before. I looked at the outcomes of patients treated for decades,” Dr. Glick recounted. Specifically, he contacted patients who had been in his care for up to 50 years. In “this naturalistic study,” he specifically asked the patients to rate their adherence to antipsychotics and to provide a global assessment of their life satisfaction, both on a scale of 1-10.

         

         


        “What I found in a relatively large sample was that the more adherent patients were to their medication, the more likely they were to report adequate satisfaction with their life,” Dr. Glick said. For those who were not adherent, life in general “has been a disaster.”

        This finding is not entirely surprising given the power of antipsychotics to change thinking. However, for those engaged in the immediate task of controlling acute symptoms, the importance of chronicity might not be given adequate emphasis. This requires educating patients and their families about the need to embark on lifetime treatment, Dr. Glick said. Like a diagnosis of diabetes, a diagnosis of schizophrenia means constant vigilance for manifestations of disease and appropriate adjustments of therapy to improve long-term outcomes.

        Since evaluating the relationship between medication adherence and long-term outcomes in patients with schizophrenia treated at Stanford, the same type of evaluation was conducted with population samples from the Veterans Affairs system and from China. The data “show exactly the same thing,” Dr. Glick said.

        It is important to use every available resource in helping patients recognize and deal with schizophrenia chronicity. In addition to engaging families, he believes that organizations such as the National Alliance on Mental Illness or NAMI, are useful sources of support.

         

         

         

        – The secret to optimal long-term disease control in schizophrenia is to implement the same type of continuous and close management provided to other chronic diseases, like hypertension or inflammatory bowel disease, according to a lecture delivered at the annual meeting of the American College of Psychiatrists.

        In the Dean Award Lecture – a talk characterized as “a stroll through the long-term understanding of the treatment of schizophrenia” – Ira D. Glick, MD, said that, although antipsychotics provide the foundation of disease control, patients and families need to understand and respect disease chronicity.

        Dr. Ira D. Glick
        Dr. Glick remembered speculation in his training that bad parenting might be a cause or contributor to the development of schizophrenia. Now, genetic susceptibility is recognized as a dominant factor for both developing the disease and determining severity, said Dr. Glick, professor emeritus in the department of psychiatry and behavioral sciences at Stanford (Calif.) University. Regardless of etiology, however, he believes that convincing patients and families that schizophrenia is a lifetime disease is a critical first step to treatment compliance that optimizes adequate symptom control.

        “In the last 5 or 6 years, I did something that no one has ever done before. I looked at the outcomes of patients treated for decades,” Dr. Glick recounted. Specifically, he contacted patients who had been in his care for up to 50 years. In “this naturalistic study,” he specifically asked the patients to rate their adherence to antipsychotics and to provide a global assessment of their life satisfaction, both on a scale of 1-10.

         

         


        “What I found in a relatively large sample was that the more adherent patients were to their medication, the more likely they were to report adequate satisfaction with their life,” Dr. Glick said. For those who were not adherent, life in general “has been a disaster.”

        This finding is not entirely surprising given the power of antipsychotics to change thinking. However, for those engaged in the immediate task of controlling acute symptoms, the importance of chronicity might not be given adequate emphasis. This requires educating patients and their families about the need to embark on lifetime treatment, Dr. Glick said. Like a diagnosis of diabetes, a diagnosis of schizophrenia means constant vigilance for manifestations of disease and appropriate adjustments of therapy to improve long-term outcomes.

        Since evaluating the relationship between medication adherence and long-term outcomes in patients with schizophrenia treated at Stanford, the same type of evaluation was conducted with population samples from the Veterans Affairs system and from China. The data “show exactly the same thing,” Dr. Glick said.

        It is important to use every available resource in helping patients recognize and deal with schizophrenia chronicity. In addition to engaging families, he believes that organizations such as the National Alliance on Mental Illness or NAMI, are useful sources of support.

         

         

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        Substance abuse among older adults: A growing problem

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        Substance abuse among older adults: A growing problem

        Baby Boomers—a term used to refer to individuals born in the United States between 1946 and 1964—are now approaching old age. Surprisingly, these older adults are using illicit substances in a pattern not seen in prior generations of older adults, including developing substance use disorders (SUDs) at increasingly higher rates; in previous generations, the prevalence of such disorders typically lowered with advancing age.

        This article discusses how to recognize and treat SUDs in older adults. Alcohol is the most commonly used substance among older adults,1 and there is a largebody of literature describing the identification and treatment of alcohol-related disorders in these patients. Therefore, this article will instead focus on older adults’ use of illicit substances, including marijuana, cocaine, and heroin.

        Epidemiology

        Prior clinical data regarding substance abuse in older adults focused on alcohol, prescription drugs, nicotine, and caffeine.2 In the past, compared with younger adults, older adults had lower rates of alcohol and other illicit drug use.3,4 Baby Boomers appear to be defying this trend.

        A 2013 Substance Abuse and Mental Health Services Administration survey found that the percentage of adults ages 50 to 64 who used illicit substances increased from 2.7% in 2002 to 6.0% in 2013.5 Specifically, during that time, past-month illicit substance use increased from 3.4% to 7.9% among those ages 50 to 54, from 1.9% to 5.7% among those ages 55 to 59, and from 2.5% to 3.9% among those ages 60 to 64.5

        More recently, a 2014 study of geriatric patients found that of the 1,302 patients age ≥65 admitted to a Level 1 trauma center, 48.3% had a positive urine drug screen.6 Someresearchers have estimated that 5.7 million older adults will require treatment for a substance use disorder in 2020, which is roughly double the 2.8 million who had an SUD in 2002 to 2006.7

        Risk factors and patterns of substance abuse

        Individual, social, and familial factors can contribute to substance use and abuse in late life. The Table1 outlines some of the potential risk factors for older adults associated with the use of illicit substances. Substance abuse among older adults can be divided into 2 broad categories: early onset (starting before age 50) and late onset (starting after age 50).8 While data are limited, in general, early-onset use is a more common pattern; late-onset use represents an estimated <10% of substance use among older adults. The factors that lead some adults to continue substance use in late life, or to begin substance use later in life, have not been thoroughly evaluated.

        Although older adults may abuse a wide variety of illicit substances, here we describe their use of marijuana, cocaine, and heroin.

         

         

        Marijuana use has changed substantially in the last decade. While marijuana is illegal under federal law, as of November 2017, 29 states had legalized marijuana for medicinal purposes and 7 states and the District of Columbia had legalized it for recreational use. The increased legal and social acceptance of marijuana has led to new businesses and methods of use beyond smoking. New types of marijuana products include edible substances, tinctures, and oils that can be vaporized and inhaled.

        In addition to euphoria and relaxation, the effects of marijuana use include increased latency time and decreased ability to respond to stimuli.2 Nonpsychiatric effects of marijuana include shallow breathing, weakened immune system, and increasing cardiac workload.2 The latter effect is especially important for older adults, many of whom may have preexisting cardiac illness and may be more likely to experience an adverse cardiac event as a result of marijuana use.2 Older adults who begin to use marijuana in late life may do so not primarily as a social activity, but more likely to experience the drug’s potentially beneficial effects on pain or appetite.2 For more on theuse of marijuana for these reasons, see “Medical marijuana: Do the benefits outweigh the risks?” in Current Psychiatry, January 2018, p. 34-41.

        Cocaine. Although cocaine is a CNS stimulant that causes a short-lived euphoria, its adverse effects impact many body systems.9 Myocardial infarction (MI) secondary to coronary artery vasospasms, stroke (hemorrhagic and ischemic), seizures, psychosis, aortic dissection, and acute renal injury are some of the most severe complications. Acute MI is the most frequent and severe cardiovascular complication seen among abusers.10 Cocaine use can cause dizziness, restlessness, headache, mydriasis, and anxiety.

        In a pilot study, Kalapatapu et al11 compared the effects of cocaine abuse in younger vs older users. They found that older users had similar patterns of cocaine abuse in terms of the amount of cocaine used and frequency of use.11 They also found that specific cognitive functions, including psychomotor speed, attention, and short-term memory, are particularly sensitive to the combined effects of aging and cocaine abuse.11

        Heroin is an opioid and a CNS depressant. Common effects include slowed heart rate, decreased blood pressure, and decreased respiration rate. Chronic heroin users show an overall decrease in immune system functioning12; this deficit might be particularly pronounced in an older person whose immune system functioning has already begun to decline as a result of aging. In recent years, as is the case with younger substance users, prescription opioids have replaced heroin as the opioid of choice among older users. However, for some early-onset heroin users, the use of this particular drug becomes well entrenched and unlikely to change, even in late life. Each year of heroin use increases the likelihood of continued use the next year by approximately 3%.2 Some research suggests that older heroin users do not decrease their use over time, and face many of the same risks as younger users, including poorer physical and mental health, severe physical disability, and mortality.13

         

         

        Challenges to recognizing the problem

        There are no screening protocols in the clinical setting that are designed specifically for detecting illicit substance abuse among older adults. Furthermore, diagnosis can be easily overlooked because the signs and symptoms of illicit substance use can be mistaken for other illnesses. To complicate matters further, older adults often do not disclose their substance use, understate it, or even try to explain away their symptoms.1 Many older adults live alone, which may increase their risk of receiving no treatment.14

        Older adults generally experience reduced tolerance to the effects of illicit substances because of age-related physiologic changes, such as decreases in renal functioning, motor functioning, and cardiac output; altered liver metabolism of certain drugs; and elevated blood glucose levels.15 As a result, symptoms of illicit substance use could be mistaken for dementia or other forms of cognitive impairment.1,16

        Although not designed specifically for older adults, an evidence-based screening instrument, such as the CAGE Questionnaire Adapted to Include Drugs, may be helpful in identifying substance abuse in these patients. Urine and/or serum drug screening, along with obtaining a comprehensive history from a trustworthy source, is useful for diagnosis.

         

        Pharmacologic treatments

        Research evaluating the use of medication for treating substance abuse specifically in older adults is extremely limited; studies have focused primarily on younger patients or mixed-age populations. Treatments that have been shown to be effective for younger patients may or may not be effective for older adults.

        Marijuana. There are no FDA-approved treatments for marijuana abuse. An open-label study found that N-acetylcysteine, 1,200 mg twice a day, resulted in a significant reduction in marijuana craving as measured by the 12-item version of the Marijuana Craving Questionnaire.17 In a double-blinded placebo-controlled study, adolescents who were dependent on marijuana who received N-acetylcysteine, 1,200 mg twice a day, were more than twice likely to stop marijuana use compared with those who received placebo.18 Some researchers have proposed that N-acetylcysteine may prevent continued use of marijuana via glutamate modulation in the nucleus accumbens. Animal models have demonstrated that chronic drug self-administration downregulates the cystine-glutamate exchanger in the nucleus accumbens, and that N-acetylcysteine upregulates this exchanger, which reduces reinstatement of drug seeking.Further studies are needed to verify this speculation.

         

         

        Cocaine. There are no FDA-approved treatments for cocaine abuse. No specific treatment approach has been found to be consistently effective.

        A potential “cocaine vaccine” called TA-CD, which is made from succinyl norcocaine conjugated to cholera toxin, is being evaluated. An initial study had promising results, finding a significant reduction in cocaine use among those who received TA-CD.19 A later double-blinded placebo-controlled study only partially replicated the efficacy found in the initial study.20

        Currently, other cocaine treatments are also being investigated. An enzyme to rapidly metabolize cocaine is being evaluated.21 So far, none of these treatments have targeted older adults, and there may be age-specific issues to consider if these approaches eventually receive FDA approval.

        Heroin. Several FDA-approved medications are available for treating dependency to heroin and other opioids, including naltrexone, buprenorphine, and methadone, but none have been studied specifically in older adults. Some studies of transdermal buprenorphine for treating chronic pain in older adults have concluded that this formulation may offer advantages for older patients.22,23 Compared with oral or sublingual buprenorphine, the transdermal formulation avoids the first-pass effect in the liver, thus greatly increasing bioavailability of the drug; avoids renal metabolism; and offers greater tolerability in patients with mild to moderate hepatic impairment.22,23 However, transdermal buprenorphine has been approved only for the treatment of pain. These beneficial aspects of transdermal buprenorphine may be applicable to older opioid users, but no age-specific studies of buprenorphine for treating opioid abuse have been conducted.

        Nonpharmacologic treatments

        The same psychotherapeutic treatments used to treat younger patients with SUDs may be appropriate for older adults. Older patients may experience feelings of isolation and shame related to needing treatment for substance abuse. These factors in treatment of older patients often are overcome by group psychotherapy. Self-help programs, such as Narcotics Anonymous or Alcoholics Anonymous, and group therapy also may be options.

         

         

        On the other hand, individual psychotherapy, such as cognitive-behavioral therapy (CBT), interpersonal therapy, and psychodynamic therapy, can provide a private and confidential environment for older adults who are less social.24

        The highly structured nature of CBT may be well suited to older adults who have memory difficulties.1 A study of 110 older veterans with substance abuse problems found evidence for the effectiveness of group CBT among these patients.25 All but 8 participants in this study were age ≥65. The intervention consisted of 16 weekly group sessions that began with analysis of substance use behavior to determine high-risk situations for use, followed by a series of modules to teach skills for coping with social pressure, being at home and alone, feelings of depression and loneliness, anxiety and tension, anger and frustration, cues for substance use, and other factors. Approximately 44% (49 of 110) completed treatment (≥13 sessions). Approximately 55% of those who completed the treatment were abstinent at 6-month follow-up.25

        Don’t assume your older patient is not using illicit substances

        It is a myth that older adults do not use and abuse illicit substances. Illicit drug use among older adults is increasing. Older adults with SUDs may not present with the same symptoms as their younger counterparts, and thus it may be difficult to identify the problem. Maintain a high index of suspicion regarding the use of illicit substances in these patients.

        Treatment options are generally limited and health care settings offer few interventions designed specifically for older adults. In general, proper identification of SUDs and targeted treatment can highly improve outcomes.

         

        Bottom Line

        The number of older adults who use illicit substances is increasing. Screening, diagnosis, and treatment of substance use disorders in these patients may be complicated by age-related factors and a lack of evidence specific to older adults. Maintaining a high index of suspicion for substance use by older adults is essential.

        Related Resource

        • Drew SM, Wilkins KM, Trevisan LA. Managing medication and alcohol misuse by your older patients. Current Psychiatry. 2010;9(2):21-24,27-28,41.

        Drug Brand Names

        Buprenorphine Buprenex, Probuphine
        Buprenorphine transdermal Butrans
        Methadone Dolophine, Methadose
        Naltrexone Revia, Vivitrol

        References

        1. Kuerbis A, Sacco P, Blazer DG, et al. Substance abuse among older adults. Clin Geriatr Med. 2014;30(3):629-654.
        2. Taylor MH, Grossberg GT. (2012). The growing problem of illicit substance abuse in the elderly: a review. Prim Care Companion CNS Disord. 2012;14(4):PCC.11r01320. doi: 10.4088/PCC.11r01320.
        3. Cummings SM, Bride B, Rawlings-Shaw AM. Alcohol abuse treatment for older adults: a review of recent empirical research. J Evid Based Soc Work. 2006;3(1):79-99.
        4. Substance Abuse and Mental Health Services Administration. Results from the 2012 national survey on drug use and health: summary of national findings, NSDUH Series H-46, HHS Publication No (SMA) 13-4795. Rockville, MD: Substance Abuse and Mental Health Service Administration; 2013.
        5. Substance Abuse and Mental Health Services Administration. Results from the 2013 national survey on drug use and health: summary of national findings. NSDUH Series H-48, HHS Publication No. (SMA) 14-4863. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2014.
        6. Ekeh AP, Parikh P, Walusimbi MS, et al. The prevalence of positive drug and alcohol screens in elderly trauma patients. Subst Abus. 2014;35(1):51-55.
        7. Wu LT, Blazer DG. Illicit and nonmedical drug use among older adults: a review. J Aging Health. 2011;23(3):481-504.
        8. Roe B, Beynon C, Pickering L, et al. Experiences of drug use and ageing: health, quality of life, relationship and service implications. J Adv Nurs. 2010;66(9):1968-1979.
        9. Zimmerman JL. Cocaine intoxication. Crit Care Clin. 2012;28(4):517-526.
        10. Weber JE, Chudnofsky CR, Boczar M, et al. Cocaine-associated chest pain: how common is myocardial infarction? Acad Emerg Med. 2000;7(8):873-877.
        11. Kalapatapu RK, Vadhan NP, Rubin E, et al. A pilot study of neurocognitive function in older and younger cocaine abusers and controls. Am J Addict. 2011;20(3):228-239.
        12. Edelman EJ, Cheng DM, Krupitsky EM, et al. Heroin use and HIV disease progression: results from a pilot study of a Russian cohort. AIDS Behav. 2015;19(6):1089-1097.
        13. Darke S, Mills KL, Ross J, et al. The ageing heroin user: career length, clinical profile and outcomes across 36 months. Drug Alcohol Rev. 2009;28(3):243-249.
        14. West LA, Cole S, Goodkind D, et al. U.S. Census Bureau, P23-212. 65+ in the United States: 2010. Washington, DC: United States Census Bureau; 2014.
        15. Boss GR, Seegmiller JE. Age-related physiological changes and their clinical significance. West J Med. 1981;135(6):434-440.
        16. Ruiz P, Strain EC, Langrod JG. The substance abuse handbook. Philadelphia, PA: Wolters Kluwer Health; 2007.
        17. Gray KM, Watson NL, Carpenter MJ, et al. N-acetylcysteine (NAC) in young marijuana users: an open-label pilot study. Am J Addict. 2010;19(2):187-189.
        18. Gray KM, Carpenter MJ, Baker NL, et al. A double-blind randomized controlled trial of N-acetylcysteine in cannabis-dependent adolescents. Am J Psychiatry. 2012;169(8):805-812.
        19. Martell BA, Orson FM, Poling J, et al. Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial. Arch Gen Psychiatry. 2009;66(10):1116-1123

        20. Kosten TR, Domingo CB, Shorter D, et al. Vaccine for cocaine dependence: a randomized double-blind placebo-controlled efficacy trial. Drug Alcohol Depend. 2014;140:42-47.
        21. Gao Y, Brimijoin S. An engineered cocaine hydrolase blunts and reverses cardiovascular responses to cocaine in rats. J Pharmacol Exp Ther. 2004;310(3):1046-1052.
        22. Vadivelu N, Hines RL. Management of chronic pain in the elderly: focus on transdermal buprenorphine. Clin Interv Aging. 2008;3(3):421-430.
        23. Al-Tawil N, Odar-Cederlöf I, Berggren AC, et al. Pharmacokinetics of transdermal buprenorphine patch in the elderly. Eur J Clin Pharmacol. 2013;69(2):143-149.
        24. Schultz SK, Arndt S, Liesveld J. Locations of facilities with special programs for older substance abuse clients in the US. Int J Geriatr Psychiatry. 2003;18(9):839-843.
        25. Schonfeld L, Dupree LW, Dickson-Fuhrman E, et al. Cognitive-behavioral treatment of older veterans with substance abuse problems. J Geriatr Psychiatry Neurol. 2000;13(3):124-129.

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        James Cho, MD
        Assistant Professor of Clinical Psychiatry
        Department of Neurology and Psychiatry
        Saint Louis University School of Medicine
        St. Louis, Missouri

        Jay Bhimani, MD
        PGY-2 Psychiatry Resident
        Morehouse School of Medicine
        Atlanta, Georgia

        Milapkumar Patel, MD 
        Associate Chief Resident
        General Psychiatry Residency Program
        Saint Louis University Hospital
        St. Louis, Missouri

        Matthew Navin Thomas, MBBS
        Kasturba Medical College, Manipal
        Manipal, India

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

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        James Cho, MD
        Assistant Professor of Clinical Psychiatry
        Department of Neurology and Psychiatry
        Saint Louis University School of Medicine
        St. Louis, Missouri

        Jay Bhimani, MD
        PGY-2 Psychiatry Resident
        Morehouse School of Medicine
        Atlanta, Georgia

        Milapkumar Patel, MD 
        Associate Chief Resident
        General Psychiatry Residency Program
        Saint Louis University Hospital
        St. Louis, Missouri

        Matthew Navin Thomas, MBBS
        Kasturba Medical College, Manipal
        Manipal, India

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

        Author and Disclosure Information

        James Cho, MD
        Assistant Professor of Clinical Psychiatry
        Department of Neurology and Psychiatry
        Saint Louis University School of Medicine
        St. Louis, Missouri

        Jay Bhimani, MD
        PGY-2 Psychiatry Resident
        Morehouse School of Medicine
        Atlanta, Georgia

        Milapkumar Patel, MD 
        Associate Chief Resident
        General Psychiatry Residency Program
        Saint Louis University Hospital
        St. Louis, Missouri

        Matthew Navin Thomas, MBBS
        Kasturba Medical College, Manipal
        Manipal, India

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

        Article PDF
        Article PDF

        Baby Boomers—a term used to refer to individuals born in the United States between 1946 and 1964—are now approaching old age. Surprisingly, these older adults are using illicit substances in a pattern not seen in prior generations of older adults, including developing substance use disorders (SUDs) at increasingly higher rates; in previous generations, the prevalence of such disorders typically lowered with advancing age.

        This article discusses how to recognize and treat SUDs in older adults. Alcohol is the most commonly used substance among older adults,1 and there is a largebody of literature describing the identification and treatment of alcohol-related disorders in these patients. Therefore, this article will instead focus on older adults’ use of illicit substances, including marijuana, cocaine, and heroin.

        Epidemiology

        Prior clinical data regarding substance abuse in older adults focused on alcohol, prescription drugs, nicotine, and caffeine.2 In the past, compared with younger adults, older adults had lower rates of alcohol and other illicit drug use.3,4 Baby Boomers appear to be defying this trend.

        A 2013 Substance Abuse and Mental Health Services Administration survey found that the percentage of adults ages 50 to 64 who used illicit substances increased from 2.7% in 2002 to 6.0% in 2013.5 Specifically, during that time, past-month illicit substance use increased from 3.4% to 7.9% among those ages 50 to 54, from 1.9% to 5.7% among those ages 55 to 59, and from 2.5% to 3.9% among those ages 60 to 64.5

        More recently, a 2014 study of geriatric patients found that of the 1,302 patients age ≥65 admitted to a Level 1 trauma center, 48.3% had a positive urine drug screen.6 Someresearchers have estimated that 5.7 million older adults will require treatment for a substance use disorder in 2020, which is roughly double the 2.8 million who had an SUD in 2002 to 2006.7

        Risk factors and patterns of substance abuse

        Individual, social, and familial factors can contribute to substance use and abuse in late life. The Table1 outlines some of the potential risk factors for older adults associated with the use of illicit substances. Substance abuse among older adults can be divided into 2 broad categories: early onset (starting before age 50) and late onset (starting after age 50).8 While data are limited, in general, early-onset use is a more common pattern; late-onset use represents an estimated <10% of substance use among older adults. The factors that lead some adults to continue substance use in late life, or to begin substance use later in life, have not been thoroughly evaluated.

        Although older adults may abuse a wide variety of illicit substances, here we describe their use of marijuana, cocaine, and heroin.

         

         

        Marijuana use has changed substantially in the last decade. While marijuana is illegal under federal law, as of November 2017, 29 states had legalized marijuana for medicinal purposes and 7 states and the District of Columbia had legalized it for recreational use. The increased legal and social acceptance of marijuana has led to new businesses and methods of use beyond smoking. New types of marijuana products include edible substances, tinctures, and oils that can be vaporized and inhaled.

        In addition to euphoria and relaxation, the effects of marijuana use include increased latency time and decreased ability to respond to stimuli.2 Nonpsychiatric effects of marijuana include shallow breathing, weakened immune system, and increasing cardiac workload.2 The latter effect is especially important for older adults, many of whom may have preexisting cardiac illness and may be more likely to experience an adverse cardiac event as a result of marijuana use.2 Older adults who begin to use marijuana in late life may do so not primarily as a social activity, but more likely to experience the drug’s potentially beneficial effects on pain or appetite.2 For more on theuse of marijuana for these reasons, see “Medical marijuana: Do the benefits outweigh the risks?” in Current Psychiatry, January 2018, p. 34-41.

        Cocaine. Although cocaine is a CNS stimulant that causes a short-lived euphoria, its adverse effects impact many body systems.9 Myocardial infarction (MI) secondary to coronary artery vasospasms, stroke (hemorrhagic and ischemic), seizures, psychosis, aortic dissection, and acute renal injury are some of the most severe complications. Acute MI is the most frequent and severe cardiovascular complication seen among abusers.10 Cocaine use can cause dizziness, restlessness, headache, mydriasis, and anxiety.

        In a pilot study, Kalapatapu et al11 compared the effects of cocaine abuse in younger vs older users. They found that older users had similar patterns of cocaine abuse in terms of the amount of cocaine used and frequency of use.11 They also found that specific cognitive functions, including psychomotor speed, attention, and short-term memory, are particularly sensitive to the combined effects of aging and cocaine abuse.11

        Heroin is an opioid and a CNS depressant. Common effects include slowed heart rate, decreased blood pressure, and decreased respiration rate. Chronic heroin users show an overall decrease in immune system functioning12; this deficit might be particularly pronounced in an older person whose immune system functioning has already begun to decline as a result of aging. In recent years, as is the case with younger substance users, prescription opioids have replaced heroin as the opioid of choice among older users. However, for some early-onset heroin users, the use of this particular drug becomes well entrenched and unlikely to change, even in late life. Each year of heroin use increases the likelihood of continued use the next year by approximately 3%.2 Some research suggests that older heroin users do not decrease their use over time, and face many of the same risks as younger users, including poorer physical and mental health, severe physical disability, and mortality.13

         

         

        Challenges to recognizing the problem

        There are no screening protocols in the clinical setting that are designed specifically for detecting illicit substance abuse among older adults. Furthermore, diagnosis can be easily overlooked because the signs and symptoms of illicit substance use can be mistaken for other illnesses. To complicate matters further, older adults often do not disclose their substance use, understate it, or even try to explain away their symptoms.1 Many older adults live alone, which may increase their risk of receiving no treatment.14

        Older adults generally experience reduced tolerance to the effects of illicit substances because of age-related physiologic changes, such as decreases in renal functioning, motor functioning, and cardiac output; altered liver metabolism of certain drugs; and elevated blood glucose levels.15 As a result, symptoms of illicit substance use could be mistaken for dementia or other forms of cognitive impairment.1,16

        Although not designed specifically for older adults, an evidence-based screening instrument, such as the CAGE Questionnaire Adapted to Include Drugs, may be helpful in identifying substance abuse in these patients. Urine and/or serum drug screening, along with obtaining a comprehensive history from a trustworthy source, is useful for diagnosis.

         

        Pharmacologic treatments

        Research evaluating the use of medication for treating substance abuse specifically in older adults is extremely limited; studies have focused primarily on younger patients or mixed-age populations. Treatments that have been shown to be effective for younger patients may or may not be effective for older adults.

        Marijuana. There are no FDA-approved treatments for marijuana abuse. An open-label study found that N-acetylcysteine, 1,200 mg twice a day, resulted in a significant reduction in marijuana craving as measured by the 12-item version of the Marijuana Craving Questionnaire.17 In a double-blinded placebo-controlled study, adolescents who were dependent on marijuana who received N-acetylcysteine, 1,200 mg twice a day, were more than twice likely to stop marijuana use compared with those who received placebo.18 Some researchers have proposed that N-acetylcysteine may prevent continued use of marijuana via glutamate modulation in the nucleus accumbens. Animal models have demonstrated that chronic drug self-administration downregulates the cystine-glutamate exchanger in the nucleus accumbens, and that N-acetylcysteine upregulates this exchanger, which reduces reinstatement of drug seeking.Further studies are needed to verify this speculation.

         

         

        Cocaine. There are no FDA-approved treatments for cocaine abuse. No specific treatment approach has been found to be consistently effective.

        A potential “cocaine vaccine” called TA-CD, which is made from succinyl norcocaine conjugated to cholera toxin, is being evaluated. An initial study had promising results, finding a significant reduction in cocaine use among those who received TA-CD.19 A later double-blinded placebo-controlled study only partially replicated the efficacy found in the initial study.20

        Currently, other cocaine treatments are also being investigated. An enzyme to rapidly metabolize cocaine is being evaluated.21 So far, none of these treatments have targeted older adults, and there may be age-specific issues to consider if these approaches eventually receive FDA approval.

        Heroin. Several FDA-approved medications are available for treating dependency to heroin and other opioids, including naltrexone, buprenorphine, and methadone, but none have been studied specifically in older adults. Some studies of transdermal buprenorphine for treating chronic pain in older adults have concluded that this formulation may offer advantages for older patients.22,23 Compared with oral or sublingual buprenorphine, the transdermal formulation avoids the first-pass effect in the liver, thus greatly increasing bioavailability of the drug; avoids renal metabolism; and offers greater tolerability in patients with mild to moderate hepatic impairment.22,23 However, transdermal buprenorphine has been approved only for the treatment of pain. These beneficial aspects of transdermal buprenorphine may be applicable to older opioid users, but no age-specific studies of buprenorphine for treating opioid abuse have been conducted.

        Nonpharmacologic treatments

        The same psychotherapeutic treatments used to treat younger patients with SUDs may be appropriate for older adults. Older patients may experience feelings of isolation and shame related to needing treatment for substance abuse. These factors in treatment of older patients often are overcome by group psychotherapy. Self-help programs, such as Narcotics Anonymous or Alcoholics Anonymous, and group therapy also may be options.

         

         

        On the other hand, individual psychotherapy, such as cognitive-behavioral therapy (CBT), interpersonal therapy, and psychodynamic therapy, can provide a private and confidential environment for older adults who are less social.24

        The highly structured nature of CBT may be well suited to older adults who have memory difficulties.1 A study of 110 older veterans with substance abuse problems found evidence for the effectiveness of group CBT among these patients.25 All but 8 participants in this study were age ≥65. The intervention consisted of 16 weekly group sessions that began with analysis of substance use behavior to determine high-risk situations for use, followed by a series of modules to teach skills for coping with social pressure, being at home and alone, feelings of depression and loneliness, anxiety and tension, anger and frustration, cues for substance use, and other factors. Approximately 44% (49 of 110) completed treatment (≥13 sessions). Approximately 55% of those who completed the treatment were abstinent at 6-month follow-up.25

        Don’t assume your older patient is not using illicit substances

        It is a myth that older adults do not use and abuse illicit substances. Illicit drug use among older adults is increasing. Older adults with SUDs may not present with the same symptoms as their younger counterparts, and thus it may be difficult to identify the problem. Maintain a high index of suspicion regarding the use of illicit substances in these patients.

        Treatment options are generally limited and health care settings offer few interventions designed specifically for older adults. In general, proper identification of SUDs and targeted treatment can highly improve outcomes.

         

        Bottom Line

        The number of older adults who use illicit substances is increasing. Screening, diagnosis, and treatment of substance use disorders in these patients may be complicated by age-related factors and a lack of evidence specific to older adults. Maintaining a high index of suspicion for substance use by older adults is essential.

        Related Resource

        • Drew SM, Wilkins KM, Trevisan LA. Managing medication and alcohol misuse by your older patients. Current Psychiatry. 2010;9(2):21-24,27-28,41.

        Drug Brand Names

        Buprenorphine Buprenex, Probuphine
        Buprenorphine transdermal Butrans
        Methadone Dolophine, Methadose
        Naltrexone Revia, Vivitrol

        Baby Boomers—a term used to refer to individuals born in the United States between 1946 and 1964—are now approaching old age. Surprisingly, these older adults are using illicit substances in a pattern not seen in prior generations of older adults, including developing substance use disorders (SUDs) at increasingly higher rates; in previous generations, the prevalence of such disorders typically lowered with advancing age.

        This article discusses how to recognize and treat SUDs in older adults. Alcohol is the most commonly used substance among older adults,1 and there is a largebody of literature describing the identification and treatment of alcohol-related disorders in these patients. Therefore, this article will instead focus on older adults’ use of illicit substances, including marijuana, cocaine, and heroin.

        Epidemiology

        Prior clinical data regarding substance abuse in older adults focused on alcohol, prescription drugs, nicotine, and caffeine.2 In the past, compared with younger adults, older adults had lower rates of alcohol and other illicit drug use.3,4 Baby Boomers appear to be defying this trend.

        A 2013 Substance Abuse and Mental Health Services Administration survey found that the percentage of adults ages 50 to 64 who used illicit substances increased from 2.7% in 2002 to 6.0% in 2013.5 Specifically, during that time, past-month illicit substance use increased from 3.4% to 7.9% among those ages 50 to 54, from 1.9% to 5.7% among those ages 55 to 59, and from 2.5% to 3.9% among those ages 60 to 64.5

        More recently, a 2014 study of geriatric patients found that of the 1,302 patients age ≥65 admitted to a Level 1 trauma center, 48.3% had a positive urine drug screen.6 Someresearchers have estimated that 5.7 million older adults will require treatment for a substance use disorder in 2020, which is roughly double the 2.8 million who had an SUD in 2002 to 2006.7

        Risk factors and patterns of substance abuse

        Individual, social, and familial factors can contribute to substance use and abuse in late life. The Table1 outlines some of the potential risk factors for older adults associated with the use of illicit substances. Substance abuse among older adults can be divided into 2 broad categories: early onset (starting before age 50) and late onset (starting after age 50).8 While data are limited, in general, early-onset use is a more common pattern; late-onset use represents an estimated <10% of substance use among older adults. The factors that lead some adults to continue substance use in late life, or to begin substance use later in life, have not been thoroughly evaluated.

        Although older adults may abuse a wide variety of illicit substances, here we describe their use of marijuana, cocaine, and heroin.

         

         

        Marijuana use has changed substantially in the last decade. While marijuana is illegal under federal law, as of November 2017, 29 states had legalized marijuana for medicinal purposes and 7 states and the District of Columbia had legalized it for recreational use. The increased legal and social acceptance of marijuana has led to new businesses and methods of use beyond smoking. New types of marijuana products include edible substances, tinctures, and oils that can be vaporized and inhaled.

        In addition to euphoria and relaxation, the effects of marijuana use include increased latency time and decreased ability to respond to stimuli.2 Nonpsychiatric effects of marijuana include shallow breathing, weakened immune system, and increasing cardiac workload.2 The latter effect is especially important for older adults, many of whom may have preexisting cardiac illness and may be more likely to experience an adverse cardiac event as a result of marijuana use.2 Older adults who begin to use marijuana in late life may do so not primarily as a social activity, but more likely to experience the drug’s potentially beneficial effects on pain or appetite.2 For more on theuse of marijuana for these reasons, see “Medical marijuana: Do the benefits outweigh the risks?” in Current Psychiatry, January 2018, p. 34-41.

        Cocaine. Although cocaine is a CNS stimulant that causes a short-lived euphoria, its adverse effects impact many body systems.9 Myocardial infarction (MI) secondary to coronary artery vasospasms, stroke (hemorrhagic and ischemic), seizures, psychosis, aortic dissection, and acute renal injury are some of the most severe complications. Acute MI is the most frequent and severe cardiovascular complication seen among abusers.10 Cocaine use can cause dizziness, restlessness, headache, mydriasis, and anxiety.

        In a pilot study, Kalapatapu et al11 compared the effects of cocaine abuse in younger vs older users. They found that older users had similar patterns of cocaine abuse in terms of the amount of cocaine used and frequency of use.11 They also found that specific cognitive functions, including psychomotor speed, attention, and short-term memory, are particularly sensitive to the combined effects of aging and cocaine abuse.11

        Heroin is an opioid and a CNS depressant. Common effects include slowed heart rate, decreased blood pressure, and decreased respiration rate. Chronic heroin users show an overall decrease in immune system functioning12; this deficit might be particularly pronounced in an older person whose immune system functioning has already begun to decline as a result of aging. In recent years, as is the case with younger substance users, prescription opioids have replaced heroin as the opioid of choice among older users. However, for some early-onset heroin users, the use of this particular drug becomes well entrenched and unlikely to change, even in late life. Each year of heroin use increases the likelihood of continued use the next year by approximately 3%.2 Some research suggests that older heroin users do not decrease their use over time, and face many of the same risks as younger users, including poorer physical and mental health, severe physical disability, and mortality.13

         

         

        Challenges to recognizing the problem

        There are no screening protocols in the clinical setting that are designed specifically for detecting illicit substance abuse among older adults. Furthermore, diagnosis can be easily overlooked because the signs and symptoms of illicit substance use can be mistaken for other illnesses. To complicate matters further, older adults often do not disclose their substance use, understate it, or even try to explain away their symptoms.1 Many older adults live alone, which may increase their risk of receiving no treatment.14

        Older adults generally experience reduced tolerance to the effects of illicit substances because of age-related physiologic changes, such as decreases in renal functioning, motor functioning, and cardiac output; altered liver metabolism of certain drugs; and elevated blood glucose levels.15 As a result, symptoms of illicit substance use could be mistaken for dementia or other forms of cognitive impairment.1,16

        Although not designed specifically for older adults, an evidence-based screening instrument, such as the CAGE Questionnaire Adapted to Include Drugs, may be helpful in identifying substance abuse in these patients. Urine and/or serum drug screening, along with obtaining a comprehensive history from a trustworthy source, is useful for diagnosis.

         

        Pharmacologic treatments

        Research evaluating the use of medication for treating substance abuse specifically in older adults is extremely limited; studies have focused primarily on younger patients or mixed-age populations. Treatments that have been shown to be effective for younger patients may or may not be effective for older adults.

        Marijuana. There are no FDA-approved treatments for marijuana abuse. An open-label study found that N-acetylcysteine, 1,200 mg twice a day, resulted in a significant reduction in marijuana craving as measured by the 12-item version of the Marijuana Craving Questionnaire.17 In a double-blinded placebo-controlled study, adolescents who were dependent on marijuana who received N-acetylcysteine, 1,200 mg twice a day, were more than twice likely to stop marijuana use compared with those who received placebo.18 Some researchers have proposed that N-acetylcysteine may prevent continued use of marijuana via glutamate modulation in the nucleus accumbens. Animal models have demonstrated that chronic drug self-administration downregulates the cystine-glutamate exchanger in the nucleus accumbens, and that N-acetylcysteine upregulates this exchanger, which reduces reinstatement of drug seeking.Further studies are needed to verify this speculation.

         

         

        Cocaine. There are no FDA-approved treatments for cocaine abuse. No specific treatment approach has been found to be consistently effective.

        A potential “cocaine vaccine” called TA-CD, which is made from succinyl norcocaine conjugated to cholera toxin, is being evaluated. An initial study had promising results, finding a significant reduction in cocaine use among those who received TA-CD.19 A later double-blinded placebo-controlled study only partially replicated the efficacy found in the initial study.20

        Currently, other cocaine treatments are also being investigated. An enzyme to rapidly metabolize cocaine is being evaluated.21 So far, none of these treatments have targeted older adults, and there may be age-specific issues to consider if these approaches eventually receive FDA approval.

        Heroin. Several FDA-approved medications are available for treating dependency to heroin and other opioids, including naltrexone, buprenorphine, and methadone, but none have been studied specifically in older adults. Some studies of transdermal buprenorphine for treating chronic pain in older adults have concluded that this formulation may offer advantages for older patients.22,23 Compared with oral or sublingual buprenorphine, the transdermal formulation avoids the first-pass effect in the liver, thus greatly increasing bioavailability of the drug; avoids renal metabolism; and offers greater tolerability in patients with mild to moderate hepatic impairment.22,23 However, transdermal buprenorphine has been approved only for the treatment of pain. These beneficial aspects of transdermal buprenorphine may be applicable to older opioid users, but no age-specific studies of buprenorphine for treating opioid abuse have been conducted.

        Nonpharmacologic treatments

        The same psychotherapeutic treatments used to treat younger patients with SUDs may be appropriate for older adults. Older patients may experience feelings of isolation and shame related to needing treatment for substance abuse. These factors in treatment of older patients often are overcome by group psychotherapy. Self-help programs, such as Narcotics Anonymous or Alcoholics Anonymous, and group therapy also may be options.

         

         

        On the other hand, individual psychotherapy, such as cognitive-behavioral therapy (CBT), interpersonal therapy, and psychodynamic therapy, can provide a private and confidential environment for older adults who are less social.24

        The highly structured nature of CBT may be well suited to older adults who have memory difficulties.1 A study of 110 older veterans with substance abuse problems found evidence for the effectiveness of group CBT among these patients.25 All but 8 participants in this study were age ≥65. The intervention consisted of 16 weekly group sessions that began with analysis of substance use behavior to determine high-risk situations for use, followed by a series of modules to teach skills for coping with social pressure, being at home and alone, feelings of depression and loneliness, anxiety and tension, anger and frustration, cues for substance use, and other factors. Approximately 44% (49 of 110) completed treatment (≥13 sessions). Approximately 55% of those who completed the treatment were abstinent at 6-month follow-up.25

        Don’t assume your older patient is not using illicit substances

        It is a myth that older adults do not use and abuse illicit substances. Illicit drug use among older adults is increasing. Older adults with SUDs may not present with the same symptoms as their younger counterparts, and thus it may be difficult to identify the problem. Maintain a high index of suspicion regarding the use of illicit substances in these patients.

        Treatment options are generally limited and health care settings offer few interventions designed specifically for older adults. In general, proper identification of SUDs and targeted treatment can highly improve outcomes.

         

        Bottom Line

        The number of older adults who use illicit substances is increasing. Screening, diagnosis, and treatment of substance use disorders in these patients may be complicated by age-related factors and a lack of evidence specific to older adults. Maintaining a high index of suspicion for substance use by older adults is essential.

        Related Resource

        • Drew SM, Wilkins KM, Trevisan LA. Managing medication and alcohol misuse by your older patients. Current Psychiatry. 2010;9(2):21-24,27-28,41.

        Drug Brand Names

        Buprenorphine Buprenex, Probuphine
        Buprenorphine transdermal Butrans
        Methadone Dolophine, Methadose
        Naltrexone Revia, Vivitrol

        References

        1. Kuerbis A, Sacco P, Blazer DG, et al. Substance abuse among older adults. Clin Geriatr Med. 2014;30(3):629-654.
        2. Taylor MH, Grossberg GT. (2012). The growing problem of illicit substance abuse in the elderly: a review. Prim Care Companion CNS Disord. 2012;14(4):PCC.11r01320. doi: 10.4088/PCC.11r01320.
        3. Cummings SM, Bride B, Rawlings-Shaw AM. Alcohol abuse treatment for older adults: a review of recent empirical research. J Evid Based Soc Work. 2006;3(1):79-99.
        4. Substance Abuse and Mental Health Services Administration. Results from the 2012 national survey on drug use and health: summary of national findings, NSDUH Series H-46, HHS Publication No (SMA) 13-4795. Rockville, MD: Substance Abuse and Mental Health Service Administration; 2013.
        5. Substance Abuse and Mental Health Services Administration. Results from the 2013 national survey on drug use and health: summary of national findings. NSDUH Series H-48, HHS Publication No. (SMA) 14-4863. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2014.
        6. Ekeh AP, Parikh P, Walusimbi MS, et al. The prevalence of positive drug and alcohol screens in elderly trauma patients. Subst Abus. 2014;35(1):51-55.
        7. Wu LT, Blazer DG. Illicit and nonmedical drug use among older adults: a review. J Aging Health. 2011;23(3):481-504.
        8. Roe B, Beynon C, Pickering L, et al. Experiences of drug use and ageing: health, quality of life, relationship and service implications. J Adv Nurs. 2010;66(9):1968-1979.
        9. Zimmerman JL. Cocaine intoxication. Crit Care Clin. 2012;28(4):517-526.
        10. Weber JE, Chudnofsky CR, Boczar M, et al. Cocaine-associated chest pain: how common is myocardial infarction? Acad Emerg Med. 2000;7(8):873-877.
        11. Kalapatapu RK, Vadhan NP, Rubin E, et al. A pilot study of neurocognitive function in older and younger cocaine abusers and controls. Am J Addict. 2011;20(3):228-239.
        12. Edelman EJ, Cheng DM, Krupitsky EM, et al. Heroin use and HIV disease progression: results from a pilot study of a Russian cohort. AIDS Behav. 2015;19(6):1089-1097.
        13. Darke S, Mills KL, Ross J, et al. The ageing heroin user: career length, clinical profile and outcomes across 36 months. Drug Alcohol Rev. 2009;28(3):243-249.
        14. West LA, Cole S, Goodkind D, et al. U.S. Census Bureau, P23-212. 65+ in the United States: 2010. Washington, DC: United States Census Bureau; 2014.
        15. Boss GR, Seegmiller JE. Age-related physiological changes and their clinical significance. West J Med. 1981;135(6):434-440.
        16. Ruiz P, Strain EC, Langrod JG. The substance abuse handbook. Philadelphia, PA: Wolters Kluwer Health; 2007.
        17. Gray KM, Watson NL, Carpenter MJ, et al. N-acetylcysteine (NAC) in young marijuana users: an open-label pilot study. Am J Addict. 2010;19(2):187-189.
        18. Gray KM, Carpenter MJ, Baker NL, et al. A double-blind randomized controlled trial of N-acetylcysteine in cannabis-dependent adolescents. Am J Psychiatry. 2012;169(8):805-812.
        19. Martell BA, Orson FM, Poling J, et al. Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial. Arch Gen Psychiatry. 2009;66(10):1116-1123

        20. Kosten TR, Domingo CB, Shorter D, et al. Vaccine for cocaine dependence: a randomized double-blind placebo-controlled efficacy trial. Drug Alcohol Depend. 2014;140:42-47.
        21. Gao Y, Brimijoin S. An engineered cocaine hydrolase blunts and reverses cardiovascular responses to cocaine in rats. J Pharmacol Exp Ther. 2004;310(3):1046-1052.
        22. Vadivelu N, Hines RL. Management of chronic pain in the elderly: focus on transdermal buprenorphine. Clin Interv Aging. 2008;3(3):421-430.
        23. Al-Tawil N, Odar-Cederlöf I, Berggren AC, et al. Pharmacokinetics of transdermal buprenorphine patch in the elderly. Eur J Clin Pharmacol. 2013;69(2):143-149.
        24. Schultz SK, Arndt S, Liesveld J. Locations of facilities with special programs for older substance abuse clients in the US. Int J Geriatr Psychiatry. 2003;18(9):839-843.
        25. Schonfeld L, Dupree LW, Dickson-Fuhrman E, et al. Cognitive-behavioral treatment of older veterans with substance abuse problems. J Geriatr Psychiatry Neurol. 2000;13(3):124-129.

        References

        1. Kuerbis A, Sacco P, Blazer DG, et al. Substance abuse among older adults. Clin Geriatr Med. 2014;30(3):629-654.
        2. Taylor MH, Grossberg GT. (2012). The growing problem of illicit substance abuse in the elderly: a review. Prim Care Companion CNS Disord. 2012;14(4):PCC.11r01320. doi: 10.4088/PCC.11r01320.
        3. Cummings SM, Bride B, Rawlings-Shaw AM. Alcohol abuse treatment for older adults: a review of recent empirical research. J Evid Based Soc Work. 2006;3(1):79-99.
        4. Substance Abuse and Mental Health Services Administration. Results from the 2012 national survey on drug use and health: summary of national findings, NSDUH Series H-46, HHS Publication No (SMA) 13-4795. Rockville, MD: Substance Abuse and Mental Health Service Administration; 2013.
        5. Substance Abuse and Mental Health Services Administration. Results from the 2013 national survey on drug use and health: summary of national findings. NSDUH Series H-48, HHS Publication No. (SMA) 14-4863. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2014.
        6. Ekeh AP, Parikh P, Walusimbi MS, et al. The prevalence of positive drug and alcohol screens in elderly trauma patients. Subst Abus. 2014;35(1):51-55.
        7. Wu LT, Blazer DG. Illicit and nonmedical drug use among older adults: a review. J Aging Health. 2011;23(3):481-504.
        8. Roe B, Beynon C, Pickering L, et al. Experiences of drug use and ageing: health, quality of life, relationship and service implications. J Adv Nurs. 2010;66(9):1968-1979.
        9. Zimmerman JL. Cocaine intoxication. Crit Care Clin. 2012;28(4):517-526.
        10. Weber JE, Chudnofsky CR, Boczar M, et al. Cocaine-associated chest pain: how common is myocardial infarction? Acad Emerg Med. 2000;7(8):873-877.
        11. Kalapatapu RK, Vadhan NP, Rubin E, et al. A pilot study of neurocognitive function in older and younger cocaine abusers and controls. Am J Addict. 2011;20(3):228-239.
        12. Edelman EJ, Cheng DM, Krupitsky EM, et al. Heroin use and HIV disease progression: results from a pilot study of a Russian cohort. AIDS Behav. 2015;19(6):1089-1097.
        13. Darke S, Mills KL, Ross J, et al. The ageing heroin user: career length, clinical profile and outcomes across 36 months. Drug Alcohol Rev. 2009;28(3):243-249.
        14. West LA, Cole S, Goodkind D, et al. U.S. Census Bureau, P23-212. 65+ in the United States: 2010. Washington, DC: United States Census Bureau; 2014.
        15. Boss GR, Seegmiller JE. Age-related physiological changes and their clinical significance. West J Med. 1981;135(6):434-440.
        16. Ruiz P, Strain EC, Langrod JG. The substance abuse handbook. Philadelphia, PA: Wolters Kluwer Health; 2007.
        17. Gray KM, Watson NL, Carpenter MJ, et al. N-acetylcysteine (NAC) in young marijuana users: an open-label pilot study. Am J Addict. 2010;19(2):187-189.
        18. Gray KM, Carpenter MJ, Baker NL, et al. A double-blind randomized controlled trial of N-acetylcysteine in cannabis-dependent adolescents. Am J Psychiatry. 2012;169(8):805-812.
        19. Martell BA, Orson FM, Poling J, et al. Cocaine vaccine for the treatment of cocaine dependence in methadone-maintained patients: a randomized, double-blind, placebo-controlled efficacy trial. Arch Gen Psychiatry. 2009;66(10):1116-1123

        20. Kosten TR, Domingo CB, Shorter D, et al. Vaccine for cocaine dependence: a randomized double-blind placebo-controlled efficacy trial. Drug Alcohol Depend. 2014;140:42-47.
        21. Gao Y, Brimijoin S. An engineered cocaine hydrolase blunts and reverses cardiovascular responses to cocaine in rats. J Pharmacol Exp Ther. 2004;310(3):1046-1052.
        22. Vadivelu N, Hines RL. Management of chronic pain in the elderly: focus on transdermal buprenorphine. Clin Interv Aging. 2008;3(3):421-430.
        23. Al-Tawil N, Odar-Cederlöf I, Berggren AC, et al. Pharmacokinetics of transdermal buprenorphine patch in the elderly. Eur J Clin Pharmacol. 2013;69(2):143-149.
        24. Schultz SK, Arndt S, Liesveld J. Locations of facilities with special programs for older substance abuse clients in the US. Int J Geriatr Psychiatry. 2003;18(9):839-843.
        25. Schonfeld L, Dupree LW, Dickson-Fuhrman E, et al. Cognitive-behavioral treatment of older veterans with substance abuse problems. J Geriatr Psychiatry Neurol. 2000;13(3):124-129.

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        Mental health apps: What to tell patients

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        Mental health apps: What to tell patients

        Have your patients asked you about smartphone apps? If they haven’t yet, they may soon, as interest in apps for mental health continues to expand. There are now >10,000 mental health–related smartphone apps.1 The rapid rise of these apps is partly due to their potential to transform a patient’s smartphone into a monitoring and therapeutic platform, capable of capturing mental health symptoms in real time and delivering on-the-go therapy. Setting aside questions about the potential of mobile health, 2 urgent questions remain for the busy psychiatrist in clinical practice: What is the current evidence base for mental health apps, and what should you tell your patients about them?

        For most apps, evidence of efficacy is limited

        While the evidence base for mental health smartphone apps continues to expand, for many of these apps, there is no evidence of effectiveness. The growing consensus is that most commercially available apps are not evidence-based and some are even dangerous. For example, researchers who examined >700 mindfulness apps on the iTunes and Google Play stores found that only 4% provided acceptable mindfulness training and education.2 Another study of 58 apps that claimed to offer sobriety assessments found that none had ever been formally evaluated.3 Evidence-based reviews of suicide prevention apps have identified potentially harmful apps,4 and studies evaluating apps for bipolar disorder5 and depression6 have yielded similar results—few have any evidence supporting their use, and some offer dangerous and harmful advice. For example, researchers found that one app for bipolar disorder advised patients who are experiencing a manic episode to drink alcohol.5 Currently, the vast majority of commercially available apps are not appropriate for clinical care. This finding is not unique to mental health; similar findings have been reported for apps for cancer.7 The bottom line is that the apps that your patients are finding, and perhaps already using, may not be useful or effective.

        However, early studies have demonstrated efficacy of some apps for several conditions, including schizophrenia,8 depression,9 anxiety disorders,10 and suicidal ideation.11 Although many of the apps evaluated in these studies are not available to the public, or still require large-scale assessment before they are ready for mainstream clinical care, this research demonstrates that mental health apps can help improve treatment outcomes. As this research develops, a wave of evidence-based and effective mental health apps may be available in the near future.

        Although it is unknown how many patients are presently using mental health apps, there is strong anecdotal evidence that an increasing number of patients who use these apps and other forms of digital technology are finding some benefits. In many cases, patients may actually be ahead of the research. For example, one study that conducted an online survey of patients with schizophrenia noted that some patients are using their smartphones to play music to help block auditory hallucinations.12

        Why online reviews are of limited use

        As this evidence continues to mature, and with an ever-growing number of mental health apps available on commercial marketplaces, busy psychiatrists need to navigate this complex space. Even psychiatrists who decide to not use apps as part of care still need to be knowledgeable about them, because patients are likely to ask about the benefits of using apps, and they will expect an informed response. How would you reply if your patient asked you about a new mood-tracking app he or she recently heard about? On what would you base your recommendation and opinion?

        Reading online app reviews for guidance is not a good solution. A recent study found little relationship between the star ratings of health apps and the quality of those apps,13 which suggests that a 5-star rating on the app store is of limited use.

        Unlike medications whose ingredients do not change over time, or manualized psychotherapies that use specific protocols, mental health apps are dynamic and constantly changing.14 Think of how often the apps on your smartphone update. Thus, the version of a mental health app that your patient downloads today may be very different from the version that received a favorable user review last month. And just as there is no single medication or therapy that is ideal for every patient, neither is there a single “best” app for all patients with the same disorder. Picking an app is a personal decision that cannot be made based on a single score or numeric rating. Furthermore, the validity of app rating systems is unclear. One study found a wide variation in the interrater reliability of measures used to evaluate apps from sources that included PsyberGuide, the Anxiety and Depression Association of America, and the research literature. Quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability.15 This means that, for example, an app that one patient finds “easy to use” may be difficult to use for another. Thus, providing patients with suggestions based on an app’s ratings may result in providing information that sounds useful, but often is misleading.

         

         

        A model for evaluating apps

        One possible solution is a risk-based and personalized assessment approach to evaluating mental health apps. Although it does not offer scoring or recommendations of specific apps, the American Psychiatric Association (APA) App Evaluation Model (Figure) provides a framework to guide discussion and informed decision-making about apps. (The authors of this article helped create this model, but receive no compensation for that volunteer work.) The pyramid shape reflects the hierarchical nature of the model. To begin the process, start at the base of the pyramid and work upward.

        Ground. First, consider the context of the app by determining basic facts, such as who made it, how much it costs, and its technology requirements. This ground layer establishes the credibility of the app’s creator by questioning his or her reputation, ability to update the app, and funding sources. Understanding the app’s business model also will help you determine whether the app will stand the test of time: Will it continue to exist next month or next year, or will a lack of reliable funding lead the vendor to abandon it?

        Risk. The next layer assesses the risk, privacy, and security features of the app. Many mental health apps actively aim to avoid falling under the jurisdiction of U.S. federal health care privacy rules, such as the Health Insurance Portability and Accountability Act of 1996, so there is no guarantee that sensitive data supplied to an app will be protected. The true cost of a “free” app often is your patient’s personal mental health information, which the app’s developer may accumulate and sell for profit. Thus, it is wise to check the privacy policy to learn where your patient’s data goes. Furthermore, patients and psychiatrists must be vigilant that malware-infected apps can be uploaded to the app store, which can further compromise privacy.16 You may be surprised to learn that many apps lack a privacy policy, which means there are no protections for personal information or safeguards against the misuse of mental health data.17 Checking that an app at least promises to digitally protect mental health data through encryption and secure storage also is a good step.

        The goal of considering these factors is not to create a score, but rather to be aware of them and consider them in the context of the specific app, patient, and clinical situation. Doing so helps determine whether the app meets the appropriate risk, privacy, and security standards for your patient.

        Evidence. The next layer of the evaluation framework is evidence. The goal is to seek an app with clinical evidence of effectiveness. Simply put, if a patient is going to use an app, he should use one that works. An app without formal evidence may be effective, but it is important to make sure the patient is aware that these claims have not been verified. Many apps claim that they offer cognitive-behavioral therapy or mindfulness therapy, but few deliver on such claims.18 It is wise to try an app before recommending it to a patient to ensure that it does what it claims it does, and does not offer dangerous or harmful recommendations.

         

         

        Ease of use. Across all health apps, there is growing recognition that most downloaded apps are never used. Patient engagement with mental health apps appears to rapidly decline over the first week of use.19 There also is emerging evidence that many apps are not user-friendly. A recent study of several common mood-tracking apps found that patients with depression had difficulty entering and accessing their data.20 Because many psychiatric disorders are chronic or last at least several months, it is especially important to consider how engaging and usable the app will be for your patient. Usability varies from patient to patient, so it is best to check directly with your patient regarding his comfort with apps and mobile technology. Offering check-ins and support to help patients keep on track with apps may be critical for successful outcomes.

        Interoperability. The final layer of the model is data sharing and interoperability. It is important to determine if the data collected or generated by the app are available to you, the patient, the treatment team, and others involved in the patient’s care. As mental health treatment moves toward integrated care, apps that fragment care (by not sharing information) impede care. Check if the app can share data with an electronic medical record, or if there is a plan to review and act on data from the app as part of your patient’s treatment plan.

        More information about the APA App Evaluation Model, including additional factors to consider within each layer, is available from the APA for free at https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/app-evaluation-model. For a sample of factors to consider when evaluating a mental health app, see the Table.

         

        A reasonable strategy

        Although the APA App Evaluation Model does not endorse any particular app, it can help guide more informed decision-making. As the evidence on mental health apps continues to evolve, it will become easier to make definitive statements on what constitutes a useful app. For now, the best strategy when discussing mental health apps with patients is to combine the use of this model with your clinical judgment.

        Bottom Line

        Apps used to enhance mental health are increasingly popular. However, for many apps, there is no evidence of efficacy, and some may offer advice that is harmful and compromise patient privacy. But some may be helpful. When discussing such apps with patients, the American Psychiatric Association App Evaluation Model can help guide discussion and informed decision-making.

        Related Resource

        Acknowledgments

        Dr. Torous receives support from the Myrtlewood Foundation and a T15 NLM training grant. The authors helped create the app evaluation model discussed in this article but received no compensation for that volunteer work.

        References

        1. Torous J, Roberts LW. Needed innovation in digital health and smartphone applications for mental health: transparency and trust. JAMA Psychiatry. 2017;74(5):437-438.
        2. Mani M, Kavanagh DJ, Hides L, et al. Review and evaluation of mindfulness-based iPhone apps. JMIR Mhealth Uhealth. 2015;3(3):e82. doi: 10.2196/mhealth.4328.
        3. Wilson H, Stoyanov SR, Gandabhai S, et al. The quality and accuracy of mobile apps to prevent driving after drinking alcohol. JMIR Mhealth Uhealth. 2016;4(3):e98. doi: 10.2196/mhealth.5961.
        4. Larsen ME, Nicholas J, Christensen H. A systematic assessment of smartphone tools for suicide prevention. PLoS One. 2016;11(4):e0152285. doi: 10.1371/journal.pone.0152285.
        5. Nicholas J, Larsen ME, Proudfoot J, et al. Mobile apps for bipolar disorder: a systematic review of features and content quality. J Med Internet Res. 2015;17(8):e198. doi: 10.2196/jmir.4581.
        6. Shen N, Levitan MJ, Johnson A, et al. Finding a depression app: a review and content analysis of the depression app marketplace. JMIR Mhealth Uhealth. 2015;3(1):e16. doi: 10.2196/mhealth.3713.
        7. Davis SW, Oakley-Girvan I. Achieving value in mobile health applications for cancer survivors. J Cancer Surviv. 2017;11(4):498-504.
        8. Ben-Zeev D, Brenner CJ, Begale M, et al. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014;40(6):1244-1253.
        9. Mohr DC, Tomasino KN, Lattie EG, et al. IntelliCare: an eclectic, skills-based app suite for the treatment of depression and anxiety. J Med Internet Res. 2017;19(1):e10. doi: 10.2196/jmir.6645.
        10. Tighe J, Shand F, Ridani R, et al. Ibobbly mobile health intervention for suicide prevention in Australian Indigenous youth: a pilot randomised controlled trial. BMJ Open. 2017;7(1):e013518. doi: 10.1136/bmjopen-2016-013518.
        11. Firth J, Torous J, Nicholas J, et al. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord. 2017;218:15-22.
        12. Gay K, Torous J, Joseph A, et al. Digital technology use among individuals with schizophrenia: results of an online survey. JMIR Mental Health. 2016;3(2):e15. doi: 10.2196/mental.5379.
        13. Singh K, Drouin K, Newmark LP, et al. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff (Millwood). 2016;35(12):2310-2318.
        14. Larsen ME, Nicholas J, Christensen H. Quantifying app store dynamics: longitudinal tracking of mental health apps. JMIR Mhealth Uhealth. 2016;4(3):e96. doi: 10.2196/mhealth.6020.
        15. Powell AC, Torous J, Chan S, et al. Interrater reliability of mHealth app rating measures: analysis of top depression and smoking cessation apps. JMIR Mhealth Uhealth. 2016;4(1):e15. doi: 10.2196/mhealth.5176.
        16. Ducklin P. Apple’s XcodeGhost malware still in the machine…. https://nakedsecurity.sophos.com/2015/11/09/apples-xcodeghost-malware-still-in-the-machine. Published November 9, 2015. Accessed May 11, 2017.
        17. Rosenfeld L, Torous J, Vahia IV. Data security and privacy in apps for dementia: an analysis of existing privacy policies. Am J Geriatr Psychiatry. 2017;25(8):873-877.
        18. Torous J, Levin ME, Ahern DK, et al. Cognitive behavioral mobile applications: clinical studies, marketplace overview, and research agenda. Cogn Behav Pract. 2017;24(2):215-225.
        19. Owen JE, Jaworski BK, Kuhn E, et al. mHealth in the wild: using novel data to examine the reach, use, and impact of PTSD coach. JMIR Ment Health. 2015;2(1):e7. doi: 10.2196/mental.3935.
        20. Sarkar U, Gourley GI, Lyles CR, et al. Usability of commercially available mobile applications for diverse patients. J Gen Intern Med. 2016;31(12):1417-1426.

        Article PDF
        Author and Disclosure Information

        John Torous, MD
        Co-Director of the Digital Psychiatry Program
        Department of Psychiatry and Division of Clinical Informatics
        Beth Israel Deaconess Medical Center
        Harvard Medical School
        Boston, Massachusetts

        John Luo, MD
        Chief Medical Information Officer
        University of California, Riverside School of Medicine
        Riverside, California

        Steven R. Chan, MD, MBA
        Clinical Informatics Fellow
        Division of Hospital Medicine and Department of Psychiatry
        University of California, San Francisco School of Medicine
        San Francisco, California

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

        Issue
        March 2018
        Publications
        Topics
        Page Number
        21-25
        Sections
        Author and Disclosure Information

        John Torous, MD
        Co-Director of the Digital Psychiatry Program
        Department of Psychiatry and Division of Clinical Informatics
        Beth Israel Deaconess Medical Center
        Harvard Medical School
        Boston, Massachusetts

        John Luo, MD
        Chief Medical Information Officer
        University of California, Riverside School of Medicine
        Riverside, California

        Steven R. Chan, MD, MBA
        Clinical Informatics Fellow
        Division of Hospital Medicine and Department of Psychiatry
        University of California, San Francisco School of Medicine
        San Francisco, California

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

        Author and Disclosure Information

        John Torous, MD
        Co-Director of the Digital Psychiatry Program
        Department of Psychiatry and Division of Clinical Informatics
        Beth Israel Deaconess Medical Center
        Harvard Medical School
        Boston, Massachusetts

        John Luo, MD
        Chief Medical Information Officer
        University of California, Riverside School of Medicine
        Riverside, California

        Steven R. Chan, MD, MBA
        Clinical Informatics Fellow
        Division of Hospital Medicine and Department of Psychiatry
        University of California, San Francisco School of Medicine
        San Francisco, California

        Disclosures
        The authors report no financial relationships with any company whose products are mentioned in this article or with manufacturers of competing products.

        Article PDF
        Article PDF

        Have your patients asked you about smartphone apps? If they haven’t yet, they may soon, as interest in apps for mental health continues to expand. There are now >10,000 mental health–related smartphone apps.1 The rapid rise of these apps is partly due to their potential to transform a patient’s smartphone into a monitoring and therapeutic platform, capable of capturing mental health symptoms in real time and delivering on-the-go therapy. Setting aside questions about the potential of mobile health, 2 urgent questions remain for the busy psychiatrist in clinical practice: What is the current evidence base for mental health apps, and what should you tell your patients about them?

        For most apps, evidence of efficacy is limited

        While the evidence base for mental health smartphone apps continues to expand, for many of these apps, there is no evidence of effectiveness. The growing consensus is that most commercially available apps are not evidence-based and some are even dangerous. For example, researchers who examined >700 mindfulness apps on the iTunes and Google Play stores found that only 4% provided acceptable mindfulness training and education.2 Another study of 58 apps that claimed to offer sobriety assessments found that none had ever been formally evaluated.3 Evidence-based reviews of suicide prevention apps have identified potentially harmful apps,4 and studies evaluating apps for bipolar disorder5 and depression6 have yielded similar results—few have any evidence supporting their use, and some offer dangerous and harmful advice. For example, researchers found that one app for bipolar disorder advised patients who are experiencing a manic episode to drink alcohol.5 Currently, the vast majority of commercially available apps are not appropriate for clinical care. This finding is not unique to mental health; similar findings have been reported for apps for cancer.7 The bottom line is that the apps that your patients are finding, and perhaps already using, may not be useful or effective.

        However, early studies have demonstrated efficacy of some apps for several conditions, including schizophrenia,8 depression,9 anxiety disorders,10 and suicidal ideation.11 Although many of the apps evaluated in these studies are not available to the public, or still require large-scale assessment before they are ready for mainstream clinical care, this research demonstrates that mental health apps can help improve treatment outcomes. As this research develops, a wave of evidence-based and effective mental health apps may be available in the near future.

        Although it is unknown how many patients are presently using mental health apps, there is strong anecdotal evidence that an increasing number of patients who use these apps and other forms of digital technology are finding some benefits. In many cases, patients may actually be ahead of the research. For example, one study that conducted an online survey of patients with schizophrenia noted that some patients are using their smartphones to play music to help block auditory hallucinations.12

        Why online reviews are of limited use

        As this evidence continues to mature, and with an ever-growing number of mental health apps available on commercial marketplaces, busy psychiatrists need to navigate this complex space. Even psychiatrists who decide to not use apps as part of care still need to be knowledgeable about them, because patients are likely to ask about the benefits of using apps, and they will expect an informed response. How would you reply if your patient asked you about a new mood-tracking app he or she recently heard about? On what would you base your recommendation and opinion?

        Reading online app reviews for guidance is not a good solution. A recent study found little relationship between the star ratings of health apps and the quality of those apps,13 which suggests that a 5-star rating on the app store is of limited use.

        Unlike medications whose ingredients do not change over time, or manualized psychotherapies that use specific protocols, mental health apps are dynamic and constantly changing.14 Think of how often the apps on your smartphone update. Thus, the version of a mental health app that your patient downloads today may be very different from the version that received a favorable user review last month. And just as there is no single medication or therapy that is ideal for every patient, neither is there a single “best” app for all patients with the same disorder. Picking an app is a personal decision that cannot be made based on a single score or numeric rating. Furthermore, the validity of app rating systems is unclear. One study found a wide variation in the interrater reliability of measures used to evaluate apps from sources that included PsyberGuide, the Anxiety and Depression Association of America, and the research literature. Quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability.15 This means that, for example, an app that one patient finds “easy to use” may be difficult to use for another. Thus, providing patients with suggestions based on an app’s ratings may result in providing information that sounds useful, but often is misleading.

         

         

        A model for evaluating apps

        One possible solution is a risk-based and personalized assessment approach to evaluating mental health apps. Although it does not offer scoring or recommendations of specific apps, the American Psychiatric Association (APA) App Evaluation Model (Figure) provides a framework to guide discussion and informed decision-making about apps. (The authors of this article helped create this model, but receive no compensation for that volunteer work.) The pyramid shape reflects the hierarchical nature of the model. To begin the process, start at the base of the pyramid and work upward.

        Ground. First, consider the context of the app by determining basic facts, such as who made it, how much it costs, and its technology requirements. This ground layer establishes the credibility of the app’s creator by questioning his or her reputation, ability to update the app, and funding sources. Understanding the app’s business model also will help you determine whether the app will stand the test of time: Will it continue to exist next month or next year, or will a lack of reliable funding lead the vendor to abandon it?

        Risk. The next layer assesses the risk, privacy, and security features of the app. Many mental health apps actively aim to avoid falling under the jurisdiction of U.S. federal health care privacy rules, such as the Health Insurance Portability and Accountability Act of 1996, so there is no guarantee that sensitive data supplied to an app will be protected. The true cost of a “free” app often is your patient’s personal mental health information, which the app’s developer may accumulate and sell for profit. Thus, it is wise to check the privacy policy to learn where your patient’s data goes. Furthermore, patients and psychiatrists must be vigilant that malware-infected apps can be uploaded to the app store, which can further compromise privacy.16 You may be surprised to learn that many apps lack a privacy policy, which means there are no protections for personal information or safeguards against the misuse of mental health data.17 Checking that an app at least promises to digitally protect mental health data through encryption and secure storage also is a good step.

        The goal of considering these factors is not to create a score, but rather to be aware of them and consider them in the context of the specific app, patient, and clinical situation. Doing so helps determine whether the app meets the appropriate risk, privacy, and security standards for your patient.

        Evidence. The next layer of the evaluation framework is evidence. The goal is to seek an app with clinical evidence of effectiveness. Simply put, if a patient is going to use an app, he should use one that works. An app without formal evidence may be effective, but it is important to make sure the patient is aware that these claims have not been verified. Many apps claim that they offer cognitive-behavioral therapy or mindfulness therapy, but few deliver on such claims.18 It is wise to try an app before recommending it to a patient to ensure that it does what it claims it does, and does not offer dangerous or harmful recommendations.

         

         

        Ease of use. Across all health apps, there is growing recognition that most downloaded apps are never used. Patient engagement with mental health apps appears to rapidly decline over the first week of use.19 There also is emerging evidence that many apps are not user-friendly. A recent study of several common mood-tracking apps found that patients with depression had difficulty entering and accessing their data.20 Because many psychiatric disorders are chronic or last at least several months, it is especially important to consider how engaging and usable the app will be for your patient. Usability varies from patient to patient, so it is best to check directly with your patient regarding his comfort with apps and mobile technology. Offering check-ins and support to help patients keep on track with apps may be critical for successful outcomes.

        Interoperability. The final layer of the model is data sharing and interoperability. It is important to determine if the data collected or generated by the app are available to you, the patient, the treatment team, and others involved in the patient’s care. As mental health treatment moves toward integrated care, apps that fragment care (by not sharing information) impede care. Check if the app can share data with an electronic medical record, or if there is a plan to review and act on data from the app as part of your patient’s treatment plan.

        More information about the APA App Evaluation Model, including additional factors to consider within each layer, is available from the APA for free at https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/app-evaluation-model. For a sample of factors to consider when evaluating a mental health app, see the Table.

         

        A reasonable strategy

        Although the APA App Evaluation Model does not endorse any particular app, it can help guide more informed decision-making. As the evidence on mental health apps continues to evolve, it will become easier to make definitive statements on what constitutes a useful app. For now, the best strategy when discussing mental health apps with patients is to combine the use of this model with your clinical judgment.

        Bottom Line

        Apps used to enhance mental health are increasingly popular. However, for many apps, there is no evidence of efficacy, and some may offer advice that is harmful and compromise patient privacy. But some may be helpful. When discussing such apps with patients, the American Psychiatric Association App Evaluation Model can help guide discussion and informed decision-making.

        Related Resource

        Acknowledgments

        Dr. Torous receives support from the Myrtlewood Foundation and a T15 NLM training grant. The authors helped create the app evaluation model discussed in this article but received no compensation for that volunteer work.

        Have your patients asked you about smartphone apps? If they haven’t yet, they may soon, as interest in apps for mental health continues to expand. There are now >10,000 mental health–related smartphone apps.1 The rapid rise of these apps is partly due to their potential to transform a patient’s smartphone into a monitoring and therapeutic platform, capable of capturing mental health symptoms in real time and delivering on-the-go therapy. Setting aside questions about the potential of mobile health, 2 urgent questions remain for the busy psychiatrist in clinical practice: What is the current evidence base for mental health apps, and what should you tell your patients about them?

        For most apps, evidence of efficacy is limited

        While the evidence base for mental health smartphone apps continues to expand, for many of these apps, there is no evidence of effectiveness. The growing consensus is that most commercially available apps are not evidence-based and some are even dangerous. For example, researchers who examined >700 mindfulness apps on the iTunes and Google Play stores found that only 4% provided acceptable mindfulness training and education.2 Another study of 58 apps that claimed to offer sobriety assessments found that none had ever been formally evaluated.3 Evidence-based reviews of suicide prevention apps have identified potentially harmful apps,4 and studies evaluating apps for bipolar disorder5 and depression6 have yielded similar results—few have any evidence supporting their use, and some offer dangerous and harmful advice. For example, researchers found that one app for bipolar disorder advised patients who are experiencing a manic episode to drink alcohol.5 Currently, the vast majority of commercially available apps are not appropriate for clinical care. This finding is not unique to mental health; similar findings have been reported for apps for cancer.7 The bottom line is that the apps that your patients are finding, and perhaps already using, may not be useful or effective.

        However, early studies have demonstrated efficacy of some apps for several conditions, including schizophrenia,8 depression,9 anxiety disorders,10 and suicidal ideation.11 Although many of the apps evaluated in these studies are not available to the public, or still require large-scale assessment before they are ready for mainstream clinical care, this research demonstrates that mental health apps can help improve treatment outcomes. As this research develops, a wave of evidence-based and effective mental health apps may be available in the near future.

        Although it is unknown how many patients are presently using mental health apps, there is strong anecdotal evidence that an increasing number of patients who use these apps and other forms of digital technology are finding some benefits. In many cases, patients may actually be ahead of the research. For example, one study that conducted an online survey of patients with schizophrenia noted that some patients are using their smartphones to play music to help block auditory hallucinations.12

        Why online reviews are of limited use

        As this evidence continues to mature, and with an ever-growing number of mental health apps available on commercial marketplaces, busy psychiatrists need to navigate this complex space. Even psychiatrists who decide to not use apps as part of care still need to be knowledgeable about them, because patients are likely to ask about the benefits of using apps, and they will expect an informed response. How would you reply if your patient asked you about a new mood-tracking app he or she recently heard about? On what would you base your recommendation and opinion?

        Reading online app reviews for guidance is not a good solution. A recent study found little relationship between the star ratings of health apps and the quality of those apps,13 which suggests that a 5-star rating on the app store is of limited use.

        Unlike medications whose ingredients do not change over time, or manualized psychotherapies that use specific protocols, mental health apps are dynamic and constantly changing.14 Think of how often the apps on your smartphone update. Thus, the version of a mental health app that your patient downloads today may be very different from the version that received a favorable user review last month. And just as there is no single medication or therapy that is ideal for every patient, neither is there a single “best” app for all patients with the same disorder. Picking an app is a personal decision that cannot be made based on a single score or numeric rating. Furthermore, the validity of app rating systems is unclear. One study found a wide variation in the interrater reliability of measures used to evaluate apps from sources that included PsyberGuide, the Anxiety and Depression Association of America, and the research literature. Quality measures such as effectiveness, ease of use, and performance had relatively poor interrater reliability.15 This means that, for example, an app that one patient finds “easy to use” may be difficult to use for another. Thus, providing patients with suggestions based on an app’s ratings may result in providing information that sounds useful, but often is misleading.

         

         

        A model for evaluating apps

        One possible solution is a risk-based and personalized assessment approach to evaluating mental health apps. Although it does not offer scoring or recommendations of specific apps, the American Psychiatric Association (APA) App Evaluation Model (Figure) provides a framework to guide discussion and informed decision-making about apps. (The authors of this article helped create this model, but receive no compensation for that volunteer work.) The pyramid shape reflects the hierarchical nature of the model. To begin the process, start at the base of the pyramid and work upward.

        Ground. First, consider the context of the app by determining basic facts, such as who made it, how much it costs, and its technology requirements. This ground layer establishes the credibility of the app’s creator by questioning his or her reputation, ability to update the app, and funding sources. Understanding the app’s business model also will help you determine whether the app will stand the test of time: Will it continue to exist next month or next year, or will a lack of reliable funding lead the vendor to abandon it?

        Risk. The next layer assesses the risk, privacy, and security features of the app. Many mental health apps actively aim to avoid falling under the jurisdiction of U.S. federal health care privacy rules, such as the Health Insurance Portability and Accountability Act of 1996, so there is no guarantee that sensitive data supplied to an app will be protected. The true cost of a “free” app often is your patient’s personal mental health information, which the app’s developer may accumulate and sell for profit. Thus, it is wise to check the privacy policy to learn where your patient’s data goes. Furthermore, patients and psychiatrists must be vigilant that malware-infected apps can be uploaded to the app store, which can further compromise privacy.16 You may be surprised to learn that many apps lack a privacy policy, which means there are no protections for personal information or safeguards against the misuse of mental health data.17 Checking that an app at least promises to digitally protect mental health data through encryption and secure storage also is a good step.

        The goal of considering these factors is not to create a score, but rather to be aware of them and consider them in the context of the specific app, patient, and clinical situation. Doing so helps determine whether the app meets the appropriate risk, privacy, and security standards for your patient.

        Evidence. The next layer of the evaluation framework is evidence. The goal is to seek an app with clinical evidence of effectiveness. Simply put, if a patient is going to use an app, he should use one that works. An app without formal evidence may be effective, but it is important to make sure the patient is aware that these claims have not been verified. Many apps claim that they offer cognitive-behavioral therapy or mindfulness therapy, but few deliver on such claims.18 It is wise to try an app before recommending it to a patient to ensure that it does what it claims it does, and does not offer dangerous or harmful recommendations.

         

         

        Ease of use. Across all health apps, there is growing recognition that most downloaded apps are never used. Patient engagement with mental health apps appears to rapidly decline over the first week of use.19 There also is emerging evidence that many apps are not user-friendly. A recent study of several common mood-tracking apps found that patients with depression had difficulty entering and accessing their data.20 Because many psychiatric disorders are chronic or last at least several months, it is especially important to consider how engaging and usable the app will be for your patient. Usability varies from patient to patient, so it is best to check directly with your patient regarding his comfort with apps and mobile technology. Offering check-ins and support to help patients keep on track with apps may be critical for successful outcomes.

        Interoperability. The final layer of the model is data sharing and interoperability. It is important to determine if the data collected or generated by the app are available to you, the patient, the treatment team, and others involved in the patient’s care. As mental health treatment moves toward integrated care, apps that fragment care (by not sharing information) impede care. Check if the app can share data with an electronic medical record, or if there is a plan to review and act on data from the app as part of your patient’s treatment plan.

        More information about the APA App Evaluation Model, including additional factors to consider within each layer, is available from the APA for free at https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/app-evaluation-model. For a sample of factors to consider when evaluating a mental health app, see the Table.

         

        A reasonable strategy

        Although the APA App Evaluation Model does not endorse any particular app, it can help guide more informed decision-making. As the evidence on mental health apps continues to evolve, it will become easier to make definitive statements on what constitutes a useful app. For now, the best strategy when discussing mental health apps with patients is to combine the use of this model with your clinical judgment.

        Bottom Line

        Apps used to enhance mental health are increasingly popular. However, for many apps, there is no evidence of efficacy, and some may offer advice that is harmful and compromise patient privacy. But some may be helpful. When discussing such apps with patients, the American Psychiatric Association App Evaluation Model can help guide discussion and informed decision-making.

        Related Resource

        Acknowledgments

        Dr. Torous receives support from the Myrtlewood Foundation and a T15 NLM training grant. The authors helped create the app evaluation model discussed in this article but received no compensation for that volunteer work.

        References

        1. Torous J, Roberts LW. Needed innovation in digital health and smartphone applications for mental health: transparency and trust. JAMA Psychiatry. 2017;74(5):437-438.
        2. Mani M, Kavanagh DJ, Hides L, et al. Review and evaluation of mindfulness-based iPhone apps. JMIR Mhealth Uhealth. 2015;3(3):e82. doi: 10.2196/mhealth.4328.
        3. Wilson H, Stoyanov SR, Gandabhai S, et al. The quality and accuracy of mobile apps to prevent driving after drinking alcohol. JMIR Mhealth Uhealth. 2016;4(3):e98. doi: 10.2196/mhealth.5961.
        4. Larsen ME, Nicholas J, Christensen H. A systematic assessment of smartphone tools for suicide prevention. PLoS One. 2016;11(4):e0152285. doi: 10.1371/journal.pone.0152285.
        5. Nicholas J, Larsen ME, Proudfoot J, et al. Mobile apps for bipolar disorder: a systematic review of features and content quality. J Med Internet Res. 2015;17(8):e198. doi: 10.2196/jmir.4581.
        6. Shen N, Levitan MJ, Johnson A, et al. Finding a depression app: a review and content analysis of the depression app marketplace. JMIR Mhealth Uhealth. 2015;3(1):e16. doi: 10.2196/mhealth.3713.
        7. Davis SW, Oakley-Girvan I. Achieving value in mobile health applications for cancer survivors. J Cancer Surviv. 2017;11(4):498-504.
        8. Ben-Zeev D, Brenner CJ, Begale M, et al. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014;40(6):1244-1253.
        9. Mohr DC, Tomasino KN, Lattie EG, et al. IntelliCare: an eclectic, skills-based app suite for the treatment of depression and anxiety. J Med Internet Res. 2017;19(1):e10. doi: 10.2196/jmir.6645.
        10. Tighe J, Shand F, Ridani R, et al. Ibobbly mobile health intervention for suicide prevention in Australian Indigenous youth: a pilot randomised controlled trial. BMJ Open. 2017;7(1):e013518. doi: 10.1136/bmjopen-2016-013518.
        11. Firth J, Torous J, Nicholas J, et al. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord. 2017;218:15-22.
        12. Gay K, Torous J, Joseph A, et al. Digital technology use among individuals with schizophrenia: results of an online survey. JMIR Mental Health. 2016;3(2):e15. doi: 10.2196/mental.5379.
        13. Singh K, Drouin K, Newmark LP, et al. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff (Millwood). 2016;35(12):2310-2318.
        14. Larsen ME, Nicholas J, Christensen H. Quantifying app store dynamics: longitudinal tracking of mental health apps. JMIR Mhealth Uhealth. 2016;4(3):e96. doi: 10.2196/mhealth.6020.
        15. Powell AC, Torous J, Chan S, et al. Interrater reliability of mHealth app rating measures: analysis of top depression and smoking cessation apps. JMIR Mhealth Uhealth. 2016;4(1):e15. doi: 10.2196/mhealth.5176.
        16. Ducklin P. Apple’s XcodeGhost malware still in the machine…. https://nakedsecurity.sophos.com/2015/11/09/apples-xcodeghost-malware-still-in-the-machine. Published November 9, 2015. Accessed May 11, 2017.
        17. Rosenfeld L, Torous J, Vahia IV. Data security and privacy in apps for dementia: an analysis of existing privacy policies. Am J Geriatr Psychiatry. 2017;25(8):873-877.
        18. Torous J, Levin ME, Ahern DK, et al. Cognitive behavioral mobile applications: clinical studies, marketplace overview, and research agenda. Cogn Behav Pract. 2017;24(2):215-225.
        19. Owen JE, Jaworski BK, Kuhn E, et al. mHealth in the wild: using novel data to examine the reach, use, and impact of PTSD coach. JMIR Ment Health. 2015;2(1):e7. doi: 10.2196/mental.3935.
        20. Sarkar U, Gourley GI, Lyles CR, et al. Usability of commercially available mobile applications for diverse patients. J Gen Intern Med. 2016;31(12):1417-1426.

        References

        1. Torous J, Roberts LW. Needed innovation in digital health and smartphone applications for mental health: transparency and trust. JAMA Psychiatry. 2017;74(5):437-438.
        2. Mani M, Kavanagh DJ, Hides L, et al. Review and evaluation of mindfulness-based iPhone apps. JMIR Mhealth Uhealth. 2015;3(3):e82. doi: 10.2196/mhealth.4328.
        3. Wilson H, Stoyanov SR, Gandabhai S, et al. The quality and accuracy of mobile apps to prevent driving after drinking alcohol. JMIR Mhealth Uhealth. 2016;4(3):e98. doi: 10.2196/mhealth.5961.
        4. Larsen ME, Nicholas J, Christensen H. A systematic assessment of smartphone tools for suicide prevention. PLoS One. 2016;11(4):e0152285. doi: 10.1371/journal.pone.0152285.
        5. Nicholas J, Larsen ME, Proudfoot J, et al. Mobile apps for bipolar disorder: a systematic review of features and content quality. J Med Internet Res. 2015;17(8):e198. doi: 10.2196/jmir.4581.
        6. Shen N, Levitan MJ, Johnson A, et al. Finding a depression app: a review and content analysis of the depression app marketplace. JMIR Mhealth Uhealth. 2015;3(1):e16. doi: 10.2196/mhealth.3713.
        7. Davis SW, Oakley-Girvan I. Achieving value in mobile health applications for cancer survivors. J Cancer Surviv. 2017;11(4):498-504.
        8. Ben-Zeev D, Brenner CJ, Begale M, et al. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014;40(6):1244-1253.
        9. Mohr DC, Tomasino KN, Lattie EG, et al. IntelliCare: an eclectic, skills-based app suite for the treatment of depression and anxiety. J Med Internet Res. 2017;19(1):e10. doi: 10.2196/jmir.6645.
        10. Tighe J, Shand F, Ridani R, et al. Ibobbly mobile health intervention for suicide prevention in Australian Indigenous youth: a pilot randomised controlled trial. BMJ Open. 2017;7(1):e013518. doi: 10.1136/bmjopen-2016-013518.
        11. Firth J, Torous J, Nicholas J, et al. Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord. 2017;218:15-22.
        12. Gay K, Torous J, Joseph A, et al. Digital technology use among individuals with schizophrenia: results of an online survey. JMIR Mental Health. 2016;3(2):e15. doi: 10.2196/mental.5379.
        13. Singh K, Drouin K, Newmark LP, et al. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff (Millwood). 2016;35(12):2310-2318.
        14. Larsen ME, Nicholas J, Christensen H. Quantifying app store dynamics: longitudinal tracking of mental health apps. JMIR Mhealth Uhealth. 2016;4(3):e96. doi: 10.2196/mhealth.6020.
        15. Powell AC, Torous J, Chan S, et al. Interrater reliability of mHealth app rating measures: analysis of top depression and smoking cessation apps. JMIR Mhealth Uhealth. 2016;4(1):e15. doi: 10.2196/mhealth.5176.
        16. Ducklin P. Apple’s XcodeGhost malware still in the machine…. https://nakedsecurity.sophos.com/2015/11/09/apples-xcodeghost-malware-still-in-the-machine. Published November 9, 2015. Accessed May 11, 2017.
        17. Rosenfeld L, Torous J, Vahia IV. Data security and privacy in apps for dementia: an analysis of existing privacy policies. Am J Geriatr Psychiatry. 2017;25(8):873-877.
        18. Torous J, Levin ME, Ahern DK, et al. Cognitive behavioral mobile applications: clinical studies, marketplace overview, and research agenda. Cogn Behav Pract. 2017;24(2):215-225.
        19. Owen JE, Jaworski BK, Kuhn E, et al. mHealth in the wild: using novel data to examine the reach, use, and impact of PTSD coach. JMIR Ment Health. 2015;2(1):e7. doi: 10.2196/mental.3935.
        20. Sarkar U, Gourley GI, Lyles CR, et al. Usability of commercially available mobile applications for diverse patients. J Gen Intern Med. 2016;31(12):1417-1426.

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        Neuromodulatory options for treatment-resistant depression

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        Neuromodulatory options for treatment-resistant depression

        The emergence of treatment-resistant depression (TRD) poses a great clinical and public health challenge. There is no clear consensus on criteria to define TRD. The criteria range from failure to respond to 4 weeks of a single antidepressant to failure to respond to a single trial of electroconvulsive therapy (ECT).1

        Neuromodulatory treatments for depression involve electrical stimulation of the brain through invasive or noninvasive methods. In this article, we discuss criteria for defining TRD, and compare the advantages and disadvantages of 4 neuromodulatory treatment options—ECT, vagus nerve stimulation (VNS), repetitive transcranial magnetic stimulation (rTMS), and deep brain stimulation (DBS)—for patients with depression who fail to respond to appropriate pharmacologic interventions (Table 1). Most of the studies we discuss selected patients who had severe depression and had not responded to numerous treatment trials.

        Defining treatment resistance

        Thase and Rush2 suggested progressive stages for categorizing TRD, ranging from Stage I (failure of at least 1 adequate trial of antidepressants) to Stage V (failure of adequate treatment with 2 selective serotonin reuptake inhibitors [SSRIs], a tricyclic antidepressant, a monoamine oxidase inhibitor, and a course of bilateral ECT). The Massachusetts General Hospital Staging Model suggested a quantitative scale to help characterize the degree of treatment resistance in which a higher score corresponds to a higher level of resistance.3 For every failed 6-week trial with adequate dose of an antidepressant, the patient is given a score of 1. The patient receives an extra .5 point for failure to respond to optimization of the dosage and augmentation with another medication. The patient also is given 3 points for failure to respond to ECT. Souery et al4,5 proposed a model in which they defined TRD as a failure to respond after ≥1 adequate antidepressant trials of ≥12 weeks.

         

        Treatment resistance often is the result of inadequate treatment of depressive symptoms. Inadequate treatment includes an inadequate dose of antidepressants and/or an inadequate duration of treatment. Treatment of depression also is often complicated by medical (cardiovascular, neurologic, endocrine disorders) and psychiatric (substance abuse disorders, personality disorders) comorbidities (Table 2). Patients with such comorbidities are at increased risk of mortality, and have lower response rates and increased morbidity.6

        Electroconvulsive therapy

        ECT involves the application of electric current to induce a self-limiting seizure. It affects multiple brain functions to produce its antidepressant effects. Patients with depression have a reduced concentration of γ-aminobutyric acid (GABA) in their plasma, CSF, and cortex. ECT increases GABAergic transmission in cortical circuits as demonstrated by increased levels of GABA in the occipital cortex, which may be responsible for ECT’s antidepressant effects.7 Sensitization of the 5-HT1A receptors and increased dopamine receptor binding in the striatum also have been associated with the antidepressant action of ECT.8 The antidepressant effects of ECT also can be attributed to increased neuroplasticity, as evidenced by increased neuro­trophic factors and cell proliferation in animal models.9 Dysfunction of the HPA axis has long been associated with depressive disorders; ECT improves this dysfunction, as evidenced by normalization of the dexamethasone suppression test in patients who receive ECT.7

        The results of neuroimaging studies exploring the effects of ECT vary widely based on the specific neuroimaging method, population, and statistical methods used to assess the changes. Some of the most consistent findings include reduced glucose metabolism in the frontal brain regions; reduced glucose metabolism in the hippocampus and medial temporal lobes; and reduction in functional connectivity in the anterior cingulate, parietal, medical frontal, and dorsolateral prefrontal cortex (DLPFC).10

        Randomized control trials (RCTs) have established the superiority of ECT over pharmacotherapy and sham ECT. Compared with other neuromodulatory treatments, ECT has higher remission rates. On average, the remission rate among patients receiving ECT whose depression did not respond to pharmacotherapy is approximately 48%; this increases to 64.9% among patients who previously had responded to a medication.11

         

         

        Some earlier trials found bilateral ECT to be more effective than unilateral ECT.12 Recent studies suggest that high-dose unilateral ECT (6 times the seizure threshold) is as effective as bilateral ECT.13 Studies have shown no significant differences in efficacy or treatment outcomes between twice- and thrice-weekly ECT regimens. Some studies suggest that twice-weekly ECT may be associated with a lower risk of short-term cognitive impairment compared with thrice-weekly ECT.14

        In highly refractory cases, the effects of ECT can be augmented by using pre-treatment strategies such as hyperventilation, which may increase the duration of the seizure, and remifentanil, which helps reduce the anticonvulsant effect of agents used for anesthesia.15 Advanced age, psychotic features, resistance to pharmacotherapy, and comorbid personality disorders predict poor response to ECT.16

        Adverse effects. Concerns about cognitive deficits secondary to ECT may curtail its use. Retrograde and anterograde amnesia are the most common deficits observed acutely after ECT.12 Other commonly affected cognitive functions include processing speed, attention/working memory, verbal and visual episodic memory, spatial problem solving, and executive functioning. The specific patterns of these deficits (in terms of duration and severity) vary between studies. In general, high-dose, thrice-weekly ECT and bilateral ECT are associated with greater cognitive deficits, whereas twice-weekly ECT and unilateral ECT are associated with a lower risk of cognitive adverse effects.12 A recent meta-analysis by Semkovska and McLoughlin17 found that most cognitive deficits seen after ECT are limited to the first 3 days after treatment. The authors of this meta-analysis concluded that these impairments improve over time and approach baseline 2 weeks after treatment. In fact, some of these impairments (processing speed, working memory, anterograde memory, and some aspects of executive function) improved beyond baseline after 15 days of treatment.17 The need for anesthesia and associated potential adverse effects also are a cause of concern with ECT.

        Combining ECT with medication. Several patient-specific factors, including medication regimen and comorbid medical conditions, need to be considered before using ECT in combination with pharmacotherapy. Although most antipsychotics are safe to use with ECT, concomitant use of agents with higher antihistaminic properties may increase the risk of delirium. The risk of delirium also is increased with the use of anticonvulsants and mood stabilizers (eg, lithium) because these agents increase the seizure threshold. The potential for drug interactions may affect the choice of the anesthetic agents. Also, SSRIs and serotonin-norepinephrine reuptake inhibitors can increase the duration of induced seizures.18

        Vagus nerve stimulation

        VNS, in which an implanted device stimulates the vagus nerve with electrical impulses, initially was used to reduce the frequency of seizures in patients with epilepsy and treatment-resistant partial onset seizures.19 VNS was FDA-approved for TRD in July 2005.20 One VNS system, the NCP System, consists of an implantable, multi-programmable generator, known as a pulse generator, that is subcutaneously placed in the anterior chest wall during an outpatient surgical procedure. Separate bipolar nerve-stimulating electrodes are surgically wrapped around the left cervical vagus nerve, and then connected to the generator via a tunneling procedure. A telemetric wand is subsequently linked to a portable computer and used to adjust stimulation parameters.21,22

         

         

        Support for using VNS for TRD came from a multitude of investigations and observations. Harden et al23 and Elger et al24 prospectively evaluated epileptic patients with standard depression symptom severity rating scales. They found that VNS was associated with statistically significant improvements in mood that were not related to reductions in seizures.23,24

        The mechanism of action of VNS is not clear. Earlier researchers had found evidence that VNS affected brain regions associated with norepinephrine25 and serotonin systems26; both of these neuro­transmitters have been implicated in the pathophysiology of depression. Positron emission tomography studies conducted during VNS treatment of epilepsy showed metabolic changes in cortical and subcortical areas of the brain, including the amygdala, hippocampus, and cingulate gyrus, all structures implicated in the pathophysiology of mood disorders.27

        Most studies conducted to evaluate the efficacy of VNS have been observational, looking at depression ratings before and after treatment with VNS. The short-term studies measured the difference in depression rating scales at baseline and after 10 weeks of treatment. In most of these studies, treatment with VNS resulted in a statistically significant drop in depression rating scales scores, such as on the Hamilton Depression Rating Scale (HAM-D). Based on the study design and number of study participants, response rates have varied from 13%28 to 40%,29 whereas remission rates have varied from 15.3%30 to 28%.31 More than one-half of the reduction in symptoms occurred after 6 weeks of treatment.30 In longer-term follow-up studies, the antidepressant effect generally was sustained over time. Response rates remained essentially unchanged, but the remission rates increased to approximately 29%.29 Only 1 RCT has compared patients with controls; it found no significant differences in the response or remission rates between active VNS and sham VNS.32 In this study, all patients had VNS implanted, but in the control group, the VNS was never turned on.32 In a meta-analysis conducted by Martin and Martín-Sánchez,33 31.8% (95% confidence interval [CI], 23.2% to 41.8%; P < .001) of patients treated with VNS had a significant reduction in HAM-D scores. The response rate in patients with TRD ranged from 27% to 37% and the remission rate was approximately 13%. In studies that followed patients over longer periods, both the remission and response rates increased over time.34

        Recent evidence suggests that the effectiveness of VNS may depend on the stimulation level. A multi-center double-blind study randomized patients to receive either a low (0.25 mA current, 130-millisecond pulse width), medium (0.5e1.0 mA, 250 millisecond), or high (1.25e1.5 mA, 250 millisecond) dose of VNS.35 Although all dose levels were associated with improvement in symptoms, a statistically significant durability in response was associated with the medium- and high-dose treatments.

        Adverse effects. VNS has no major adverse effects on cognitive functioning, and some studies have found improvement in executive functioning that corresponded to improvement in depressive symptoms.30 VNS also may result in improved sleep patterns as evidenced by EEG changes.31 The most commonly reported adverse effects include pain in the incision site, hoarseness of voice, throat pain, and neck pain.36

         

         

        Repetitive transcranial magnetic stimulation

        rTMS is a noninvasive technique that uses high-intensity magnetic impulses to stimulate cortical neurons. A magnetic field is produced when current passes through a coil, which in turn causes electrical stimulation in the cortical neurons that results in transient changes in the excitability of the cortical neurons.37 Although many stimulation parameters exist for TMS, high-frequency stimulation to the left prefrontal cortex (HFL-rTMS) and low-frequency stimulation to the right prefrontal cortex (LFR-rTMS) have been shown most efficacious for treating depression.38 High-frequency (5 Hz to 20 Hz) stimulation using rTMS increases cortical neuron excitability, whereas low-frequency (approximately 1 Hz) is associated with reduced cortical neuron excitability.39 The choice of targeting the DLPFC stems from a large body of functional neuroimaging studies that have shown reduction in activity/blood flow in the left DLPFC and abnormal activity/blood flow in the right DLPFC.40

        There is no dearth of RCTs evaluating the efficacy of rTMS vs sham rTMS (where no magnetic stimulation was provided). In a meta-analysis of 8 RCTs, low-frequency rTMS applied to the right DLPFC was associated with a remission rate of approximately 34.6%, compared with a 9.7% remission rate with sham rTMS.41 A response rate of approximately 38.2% was observed with HFL-rTMS, compared with a response rate of 15.1% for sham rTMS.41

        Gaynes et al42 conducted a meta-analysis to determine the efficacy of rTMS in TRD. They found that for patients with TRD, rTMs produced a response rate of 29% and a remission rate of 30%. In long-term, naturalistic, observational studies, the response rates and remission rates were much higher (58% and 37.1%, respectively).43 Over a 1-year follow-up, almost two-thirds of patients continued to meet criteria for response to treatment.44 Trials comparing HFL-rTMS and LFR-rTMS have found no significant differences in efficacy.45

        Advanced age, psychotic symptoms, and a longer duration of the current depressive episode predict poor response to rTMS. Also, imaging studies have shown that a lower metabolism in cerebellar, temporal, anterior cingulate, and occipital parts of the brain correlate with better response to HFL-rTMS.46,47

        Adverse effects. The major adverse effect associated with rTMS is the risk of inducing seizures, which is more commonly associated with high-frequency rTMS. Other common adverse effects include headache, facial muscle twitching, and tinnitus.37

         

         

        Deep brain stimulation

        DBS is an invasive stereotactic surgical procedure. It involves unilateral or bilateral placement of electrodes at neuroanatomical locations to deliver continuous stimulation from a subcutaneously implanted pulse generator.48 In the past, destructive surgical procedures were used to treat intractable depression. Surgeries such as anterior cingulotomy, anterior capsulotomy, subcaudate tractotomy, and limbic leucotomy have been shown to effectively reduce depressive symptoms.49 The advantages of DBS over destructive procedures include the fact that DBS is reversible and that the stimulation levels can easily be adjusted, and the treatment can easily be stopped or restarted.

        There is no consensus on the optimal anatomic locations for the electrode implantation in DBS. Electrodes have been implanted in the subcallosal cingulate gyrus, inferior thalamic peduncle, ventral capsule/ventral striatum, superolateral branch of the medial forebrain bundle (MFB), and nucleus accumbens.

        The choice of anatomic locations stems from the large body of neuroimaging literature characterizing functional changes associated with acute depression and response to treatment. The electrode placement targets “nodes” that form an integral part of the affected neural circuits that are responsible for regulating depressive symptoms.50 Increased metabolic activity and blood flow to the subgenual cingulate gyrus and reduction in the blood flow to the DLPFC and the striatum have been associated with active depressed states. Response to antidepressant treatment has been associated with reversal of these findings.51 Functional magnetic resonance imaging studies have consistently shown increased activity in the amygdala in response to negative stimuli among patients with depression.

        Regardless of the site of electrode placement, studies have reported symptomatic improvement among patients with depression who are treated with DBS. In 2 case reports, the electrode was implanted in the inferior thalamic peduncle.52,53 Each study had 1 participant, and each patient remitted.52,53

        Placement of the electrodes in the nucleus accumbens resulted in a response rate of 45% in 1 study,54 whereas in a different study, all patients reported improvement in anhedonia.55 A response rate of 71% and a remission rate of 35% were observed in a study in which the electrode was implanted in the ventral capsule/ventral striatum area.56

         

         

        Berlim et al57 published a systematic review and exploratory meta-analysis of studies in which the electrode had been implanted in the subgenual cingulate cortex. At 12 months, the response rate was 39.9% (95% CI, 28.4% to 52.8%), and 26.3% (95% CI, 13% to 45.9%) of patients achieved remission. The most significant drop in depression scores was observed 3 to 6 months after the surgery. No significant change in scores was observed between 6 to 12 months after surgery.57

        The MFB, specifically the superolateral branch, is emerging as an exciting new target for electrode placement in DBS. Schlaepfer et al58 studied the effects of electrodes implanted bilaterally in the superolateral branch of the MFB. They observed an almost 50% reduction in symptoms by Day 7, and at the last follow-up visit (12 to 33 weeks) 4 of the 6 patients had achieved remission.58 In a recent systematic review, Gálvez et al59 found most studies had high response/remission rates without any significant adverse effects. In a recent study of DBS targeting the MFB, 3 of 4 patients had a >50% reduction in Montgomery-Åsberg Depression Rating Scale scores at the end of first week. Although 1 patient withdrew, 2 of the other 3 patients continued to report a >80% reduction in depressive symptoms, even at Week 26.60

        Accurate localization of target areas (white matter tracts) and subsequent electrode placement might be an important factor governing treatment response. Riva-Posse et al61 found that clinical response was seen when the electrodes stimulated 3 specific white matter bundles. Interestingly, nonresponders were converted to responders simply by changing the position of the electrodes to include these white matter tracts.61

        Adverse effects. The most common adverse effects noted during studies of DBS include pain at the site of implantation and wound infection. Other adverse effects include lead fracture, transient dysphagia, and other hardware-related problems.49

         

         

        Sorting out the evidence

        In the absence of head-to-head trials, it is difficult to establish a hierarchal algorithm for use of the 4 neuromodulatory treatments discussed in the article. If we were to base our decision solely on the current literature, ECT by far has the most evidence and highest remission rates.11 We can reduce the risk of cognitive deficits by using twice-weekly instead of thrice-weekly ECT, or by using unilateral instead of bilateral ECT.12 Another strategy for reducing adverse effects associated with long-term maintenance ECT is by using it in combination with VNS. ECT and VNS can be used safely concomitantly; ECT can be used to treat acutely worsening depression, and VNS for maintaining the antidepressant effect.62

        Aside from ECT, rTMS is the only other treatment that has evidence from RCTs. Although the remission rates are not as high as ECT, its preferable adverse effects profile, noninvasive nature, and comparative low cost (compared with surgical procedures) make it a favorable choice. The Canadian Network for Mood and Anxiety Treatment guidelines suggest rTMS as the first-line treatment for patients who do not respond to pharmacologic treatments.63 ECT can be considered second-line treatment unless the patient has acute suicidal ideation, catatonia, psychotic features, greater treatment resistance, or physical deterioration, in which case ECT should be tried before TMS.63

        Among the invasive options, VNS has more evidence and is FDA-approved for TRD. However, DBS has shown great promise in early studies, with remission rates as high as 35%.56 DBS has the advantage of being reversible, and the amount of stimulation can be adjusted easily. Despite early promise, more research is needed before DBS can be widely used in clinical settings.

        Bottom Line

        When considering neuromodulatory treatments for patients with TRD, current evidence suggests electroconvulsive therapy and repetitive transcranial magnetic stimulation are preferable options. Vagus nerve stimulation and deep brain stimulation have also shown promise.

        Related Resource

        • Bewernick B, Schlaepfer TE. Update on neuromodulation for treatment-resistant depression. 2015;4. doi: 10.12688/f1000research.6633.1.

        Drug Brand Names

        Lithium Eskalith, Lithobid
        Remifentanil Ultiva

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        55. Schlaepfer TE, Bewernick BH, Kayser S, et al. Deep brain stimulation of the human reward system for major depression—rationale, outcomes and outlook. Neuropsychopharmacology. 2014;39(6):1303-1314.
        56. Malone DA Jr, Dougherty DD, Rezai AR, et al. Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biol Psychiatry. 2009;65(4):267-275.
        57. Berlim MT, McGirr A, Van den Eynde F, et al. Effectiveness and acceptability of deep brain stimulation (DBS) of the subgenual cingulate cortex for treatment-resistant depression: a systematic review and exploratory meta-analysis. J Affect Disord. 2014;159:31-38.
        58. Schlaepfer TE, Bewernick BH, Kayser S, et al. Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73(12):1204-1212.
        59. Gálvez JF, Keser Z, Mwangi B, et al. The medial forebrain bundle as a deep brain stimulation target for treatment resistant depression: a review of published data. Prog Neuropsychopharmacol Biol Psychiatry. 2015;58:59-70.
        60. Fenoy AJ, Schulz P, Selvaraj. Deep brain stimulation of the medial forebrain bundle: distinctive responses in resistant depression. J Affect Disord. 2016;203:143-151.
        61. Riva-Posse P, Choi KS, Holtzheimer PE, et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2014;76(12):963-969.
        62. Burke MJ, Husain MM. Concomitant use of vagus nerve stimulation and electroconvulsive therapy for treatment-resistant depression. J ECT. 2006;22(3):218-222.
        63. Milev R V, Giacobbe P, Kennedy SH, et al; CANMAT Depression Work Group. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: section 4. Neurostimulation treatments. Can J Psychiatry. 2016;61:561-575.

        Article PDF
        Author and Disclosure Information

        Manu Suresh Sharma, MD
        PGY-4 Resident

        Michael Ang-Rabanes, MD
        Assistant Professor

        Salih Selek, MD
        Assistant Professor

        Prashant Gajwani, MD
        Associate Professor

        Jair C. Soares, MD, PhD
        Professor and Chair

        • • • •

        Department of Psychiatry
        University of Texas Health Science Center at Houston
        Houston, Texas

        Disclosures
        Dr. Gajwani is a speaker for Merck and Sunovion. Dr. Soares receives grant/research support from Alkermes, Allergan, Bristol-Myers Squibb, Johnson & Johnson, and Merck; and serves as a consultant to Abbott, Astellas, Daiichi, and Pfizer. Drs. Sharma, Ang-Rabanes, and Selek report no financial relationships with any companies whose products are mentioned in this article or with manufacturers of competing products.

        Issue
        March 2018
        Publications
        Topics
        Page Number
        26-28,33-37
        Sections
        Author and Disclosure Information

        Manu Suresh Sharma, MD
        PGY-4 Resident

        Michael Ang-Rabanes, MD
        Assistant Professor

        Salih Selek, MD
        Assistant Professor

        Prashant Gajwani, MD
        Associate Professor

        Jair C. Soares, MD, PhD
        Professor and Chair

        • • • •

        Department of Psychiatry
        University of Texas Health Science Center at Houston
        Houston, Texas

        Disclosures
        Dr. Gajwani is a speaker for Merck and Sunovion. Dr. Soares receives grant/research support from Alkermes, Allergan, Bristol-Myers Squibb, Johnson & Johnson, and Merck; and serves as a consultant to Abbott, Astellas, Daiichi, and Pfizer. Drs. Sharma, Ang-Rabanes, and Selek report no financial relationships with any companies whose products are mentioned in this article or with manufacturers of competing products.

        Author and Disclosure Information

        Manu Suresh Sharma, MD
        PGY-4 Resident

        Michael Ang-Rabanes, MD
        Assistant Professor

        Salih Selek, MD
        Assistant Professor

        Prashant Gajwani, MD
        Associate Professor

        Jair C. Soares, MD, PhD
        Professor and Chair

        • • • •

        Department of Psychiatry
        University of Texas Health Science Center at Houston
        Houston, Texas

        Disclosures
        Dr. Gajwani is a speaker for Merck and Sunovion. Dr. Soares receives grant/research support from Alkermes, Allergan, Bristol-Myers Squibb, Johnson & Johnson, and Merck; and serves as a consultant to Abbott, Astellas, Daiichi, and Pfizer. Drs. Sharma, Ang-Rabanes, and Selek report no financial relationships with any companies whose products are mentioned in this article or with manufacturers of competing products.

        Article PDF
        Article PDF

        The emergence of treatment-resistant depression (TRD) poses a great clinical and public health challenge. There is no clear consensus on criteria to define TRD. The criteria range from failure to respond to 4 weeks of a single antidepressant to failure to respond to a single trial of electroconvulsive therapy (ECT).1

        Neuromodulatory treatments for depression involve electrical stimulation of the brain through invasive or noninvasive methods. In this article, we discuss criteria for defining TRD, and compare the advantages and disadvantages of 4 neuromodulatory treatment options—ECT, vagus nerve stimulation (VNS), repetitive transcranial magnetic stimulation (rTMS), and deep brain stimulation (DBS)—for patients with depression who fail to respond to appropriate pharmacologic interventions (Table 1). Most of the studies we discuss selected patients who had severe depression and had not responded to numerous treatment trials.

        Defining treatment resistance

        Thase and Rush2 suggested progressive stages for categorizing TRD, ranging from Stage I (failure of at least 1 adequate trial of antidepressants) to Stage V (failure of adequate treatment with 2 selective serotonin reuptake inhibitors [SSRIs], a tricyclic antidepressant, a monoamine oxidase inhibitor, and a course of bilateral ECT). The Massachusetts General Hospital Staging Model suggested a quantitative scale to help characterize the degree of treatment resistance in which a higher score corresponds to a higher level of resistance.3 For every failed 6-week trial with adequate dose of an antidepressant, the patient is given a score of 1. The patient receives an extra .5 point for failure to respond to optimization of the dosage and augmentation with another medication. The patient also is given 3 points for failure to respond to ECT. Souery et al4,5 proposed a model in which they defined TRD as a failure to respond after ≥1 adequate antidepressant trials of ≥12 weeks.

         

        Treatment resistance often is the result of inadequate treatment of depressive symptoms. Inadequate treatment includes an inadequate dose of antidepressants and/or an inadequate duration of treatment. Treatment of depression also is often complicated by medical (cardiovascular, neurologic, endocrine disorders) and psychiatric (substance abuse disorders, personality disorders) comorbidities (Table 2). Patients with such comorbidities are at increased risk of mortality, and have lower response rates and increased morbidity.6

        Electroconvulsive therapy

        ECT involves the application of electric current to induce a self-limiting seizure. It affects multiple brain functions to produce its antidepressant effects. Patients with depression have a reduced concentration of γ-aminobutyric acid (GABA) in their plasma, CSF, and cortex. ECT increases GABAergic transmission in cortical circuits as demonstrated by increased levels of GABA in the occipital cortex, which may be responsible for ECT’s antidepressant effects.7 Sensitization of the 5-HT1A receptors and increased dopamine receptor binding in the striatum also have been associated with the antidepressant action of ECT.8 The antidepressant effects of ECT also can be attributed to increased neuroplasticity, as evidenced by increased neuro­trophic factors and cell proliferation in animal models.9 Dysfunction of the HPA axis has long been associated with depressive disorders; ECT improves this dysfunction, as evidenced by normalization of the dexamethasone suppression test in patients who receive ECT.7

        The results of neuroimaging studies exploring the effects of ECT vary widely based on the specific neuroimaging method, population, and statistical methods used to assess the changes. Some of the most consistent findings include reduced glucose metabolism in the frontal brain regions; reduced glucose metabolism in the hippocampus and medial temporal lobes; and reduction in functional connectivity in the anterior cingulate, parietal, medical frontal, and dorsolateral prefrontal cortex (DLPFC).10

        Randomized control trials (RCTs) have established the superiority of ECT over pharmacotherapy and sham ECT. Compared with other neuromodulatory treatments, ECT has higher remission rates. On average, the remission rate among patients receiving ECT whose depression did not respond to pharmacotherapy is approximately 48%; this increases to 64.9% among patients who previously had responded to a medication.11

         

         

        Some earlier trials found bilateral ECT to be more effective than unilateral ECT.12 Recent studies suggest that high-dose unilateral ECT (6 times the seizure threshold) is as effective as bilateral ECT.13 Studies have shown no significant differences in efficacy or treatment outcomes between twice- and thrice-weekly ECT regimens. Some studies suggest that twice-weekly ECT may be associated with a lower risk of short-term cognitive impairment compared with thrice-weekly ECT.14

        In highly refractory cases, the effects of ECT can be augmented by using pre-treatment strategies such as hyperventilation, which may increase the duration of the seizure, and remifentanil, which helps reduce the anticonvulsant effect of agents used for anesthesia.15 Advanced age, psychotic features, resistance to pharmacotherapy, and comorbid personality disorders predict poor response to ECT.16

        Adverse effects. Concerns about cognitive deficits secondary to ECT may curtail its use. Retrograde and anterograde amnesia are the most common deficits observed acutely after ECT.12 Other commonly affected cognitive functions include processing speed, attention/working memory, verbal and visual episodic memory, spatial problem solving, and executive functioning. The specific patterns of these deficits (in terms of duration and severity) vary between studies. In general, high-dose, thrice-weekly ECT and bilateral ECT are associated with greater cognitive deficits, whereas twice-weekly ECT and unilateral ECT are associated with a lower risk of cognitive adverse effects.12 A recent meta-analysis by Semkovska and McLoughlin17 found that most cognitive deficits seen after ECT are limited to the first 3 days after treatment. The authors of this meta-analysis concluded that these impairments improve over time and approach baseline 2 weeks after treatment. In fact, some of these impairments (processing speed, working memory, anterograde memory, and some aspects of executive function) improved beyond baseline after 15 days of treatment.17 The need for anesthesia and associated potential adverse effects also are a cause of concern with ECT.

        Combining ECT with medication. Several patient-specific factors, including medication regimen and comorbid medical conditions, need to be considered before using ECT in combination with pharmacotherapy. Although most antipsychotics are safe to use with ECT, concomitant use of agents with higher antihistaminic properties may increase the risk of delirium. The risk of delirium also is increased with the use of anticonvulsants and mood stabilizers (eg, lithium) because these agents increase the seizure threshold. The potential for drug interactions may affect the choice of the anesthetic agents. Also, SSRIs and serotonin-norepinephrine reuptake inhibitors can increase the duration of induced seizures.18

        Vagus nerve stimulation

        VNS, in which an implanted device stimulates the vagus nerve with electrical impulses, initially was used to reduce the frequency of seizures in patients with epilepsy and treatment-resistant partial onset seizures.19 VNS was FDA-approved for TRD in July 2005.20 One VNS system, the NCP System, consists of an implantable, multi-programmable generator, known as a pulse generator, that is subcutaneously placed in the anterior chest wall during an outpatient surgical procedure. Separate bipolar nerve-stimulating electrodes are surgically wrapped around the left cervical vagus nerve, and then connected to the generator via a tunneling procedure. A telemetric wand is subsequently linked to a portable computer and used to adjust stimulation parameters.21,22

         

         

        Support for using VNS for TRD came from a multitude of investigations and observations. Harden et al23 and Elger et al24 prospectively evaluated epileptic patients with standard depression symptom severity rating scales. They found that VNS was associated with statistically significant improvements in mood that were not related to reductions in seizures.23,24

        The mechanism of action of VNS is not clear. Earlier researchers had found evidence that VNS affected brain regions associated with norepinephrine25 and serotonin systems26; both of these neuro­transmitters have been implicated in the pathophysiology of depression. Positron emission tomography studies conducted during VNS treatment of epilepsy showed metabolic changes in cortical and subcortical areas of the brain, including the amygdala, hippocampus, and cingulate gyrus, all structures implicated in the pathophysiology of mood disorders.27

        Most studies conducted to evaluate the efficacy of VNS have been observational, looking at depression ratings before and after treatment with VNS. The short-term studies measured the difference in depression rating scales at baseline and after 10 weeks of treatment. In most of these studies, treatment with VNS resulted in a statistically significant drop in depression rating scales scores, such as on the Hamilton Depression Rating Scale (HAM-D). Based on the study design and number of study participants, response rates have varied from 13%28 to 40%,29 whereas remission rates have varied from 15.3%30 to 28%.31 More than one-half of the reduction in symptoms occurred after 6 weeks of treatment.30 In longer-term follow-up studies, the antidepressant effect generally was sustained over time. Response rates remained essentially unchanged, but the remission rates increased to approximately 29%.29 Only 1 RCT has compared patients with controls; it found no significant differences in the response or remission rates between active VNS and sham VNS.32 In this study, all patients had VNS implanted, but in the control group, the VNS was never turned on.32 In a meta-analysis conducted by Martin and Martín-Sánchez,33 31.8% (95% confidence interval [CI], 23.2% to 41.8%; P < .001) of patients treated with VNS had a significant reduction in HAM-D scores. The response rate in patients with TRD ranged from 27% to 37% and the remission rate was approximately 13%. In studies that followed patients over longer periods, both the remission and response rates increased over time.34

        Recent evidence suggests that the effectiveness of VNS may depend on the stimulation level. A multi-center double-blind study randomized patients to receive either a low (0.25 mA current, 130-millisecond pulse width), medium (0.5e1.0 mA, 250 millisecond), or high (1.25e1.5 mA, 250 millisecond) dose of VNS.35 Although all dose levels were associated with improvement in symptoms, a statistically significant durability in response was associated with the medium- and high-dose treatments.

        Adverse effects. VNS has no major adverse effects on cognitive functioning, and some studies have found improvement in executive functioning that corresponded to improvement in depressive symptoms.30 VNS also may result in improved sleep patterns as evidenced by EEG changes.31 The most commonly reported adverse effects include pain in the incision site, hoarseness of voice, throat pain, and neck pain.36

         

         

        Repetitive transcranial magnetic stimulation

        rTMS is a noninvasive technique that uses high-intensity magnetic impulses to stimulate cortical neurons. A magnetic field is produced when current passes through a coil, which in turn causes electrical stimulation in the cortical neurons that results in transient changes in the excitability of the cortical neurons.37 Although many stimulation parameters exist for TMS, high-frequency stimulation to the left prefrontal cortex (HFL-rTMS) and low-frequency stimulation to the right prefrontal cortex (LFR-rTMS) have been shown most efficacious for treating depression.38 High-frequency (5 Hz to 20 Hz) stimulation using rTMS increases cortical neuron excitability, whereas low-frequency (approximately 1 Hz) is associated with reduced cortical neuron excitability.39 The choice of targeting the DLPFC stems from a large body of functional neuroimaging studies that have shown reduction in activity/blood flow in the left DLPFC and abnormal activity/blood flow in the right DLPFC.40

        There is no dearth of RCTs evaluating the efficacy of rTMS vs sham rTMS (where no magnetic stimulation was provided). In a meta-analysis of 8 RCTs, low-frequency rTMS applied to the right DLPFC was associated with a remission rate of approximately 34.6%, compared with a 9.7% remission rate with sham rTMS.41 A response rate of approximately 38.2% was observed with HFL-rTMS, compared with a response rate of 15.1% for sham rTMS.41

        Gaynes et al42 conducted a meta-analysis to determine the efficacy of rTMS in TRD. They found that for patients with TRD, rTMs produced a response rate of 29% and a remission rate of 30%. In long-term, naturalistic, observational studies, the response rates and remission rates were much higher (58% and 37.1%, respectively).43 Over a 1-year follow-up, almost two-thirds of patients continued to meet criteria for response to treatment.44 Trials comparing HFL-rTMS and LFR-rTMS have found no significant differences in efficacy.45

        Advanced age, psychotic symptoms, and a longer duration of the current depressive episode predict poor response to rTMS. Also, imaging studies have shown that a lower metabolism in cerebellar, temporal, anterior cingulate, and occipital parts of the brain correlate with better response to HFL-rTMS.46,47

        Adverse effects. The major adverse effect associated with rTMS is the risk of inducing seizures, which is more commonly associated with high-frequency rTMS. Other common adverse effects include headache, facial muscle twitching, and tinnitus.37

         

         

        Deep brain stimulation

        DBS is an invasive stereotactic surgical procedure. It involves unilateral or bilateral placement of electrodes at neuroanatomical locations to deliver continuous stimulation from a subcutaneously implanted pulse generator.48 In the past, destructive surgical procedures were used to treat intractable depression. Surgeries such as anterior cingulotomy, anterior capsulotomy, subcaudate tractotomy, and limbic leucotomy have been shown to effectively reduce depressive symptoms.49 The advantages of DBS over destructive procedures include the fact that DBS is reversible and that the stimulation levels can easily be adjusted, and the treatment can easily be stopped or restarted.

        There is no consensus on the optimal anatomic locations for the electrode implantation in DBS. Electrodes have been implanted in the subcallosal cingulate gyrus, inferior thalamic peduncle, ventral capsule/ventral striatum, superolateral branch of the medial forebrain bundle (MFB), and nucleus accumbens.

        The choice of anatomic locations stems from the large body of neuroimaging literature characterizing functional changes associated with acute depression and response to treatment. The electrode placement targets “nodes” that form an integral part of the affected neural circuits that are responsible for regulating depressive symptoms.50 Increased metabolic activity and blood flow to the subgenual cingulate gyrus and reduction in the blood flow to the DLPFC and the striatum have been associated with active depressed states. Response to antidepressant treatment has been associated with reversal of these findings.51 Functional magnetic resonance imaging studies have consistently shown increased activity in the amygdala in response to negative stimuli among patients with depression.

        Regardless of the site of electrode placement, studies have reported symptomatic improvement among patients with depression who are treated with DBS. In 2 case reports, the electrode was implanted in the inferior thalamic peduncle.52,53 Each study had 1 participant, and each patient remitted.52,53

        Placement of the electrodes in the nucleus accumbens resulted in a response rate of 45% in 1 study,54 whereas in a different study, all patients reported improvement in anhedonia.55 A response rate of 71% and a remission rate of 35% were observed in a study in which the electrode was implanted in the ventral capsule/ventral striatum area.56

         

         

        Berlim et al57 published a systematic review and exploratory meta-analysis of studies in which the electrode had been implanted in the subgenual cingulate cortex. At 12 months, the response rate was 39.9% (95% CI, 28.4% to 52.8%), and 26.3% (95% CI, 13% to 45.9%) of patients achieved remission. The most significant drop in depression scores was observed 3 to 6 months after the surgery. No significant change in scores was observed between 6 to 12 months after surgery.57

        The MFB, specifically the superolateral branch, is emerging as an exciting new target for electrode placement in DBS. Schlaepfer et al58 studied the effects of electrodes implanted bilaterally in the superolateral branch of the MFB. They observed an almost 50% reduction in symptoms by Day 7, and at the last follow-up visit (12 to 33 weeks) 4 of the 6 patients had achieved remission.58 In a recent systematic review, Gálvez et al59 found most studies had high response/remission rates without any significant adverse effects. In a recent study of DBS targeting the MFB, 3 of 4 patients had a >50% reduction in Montgomery-Åsberg Depression Rating Scale scores at the end of first week. Although 1 patient withdrew, 2 of the other 3 patients continued to report a >80% reduction in depressive symptoms, even at Week 26.60

        Accurate localization of target areas (white matter tracts) and subsequent electrode placement might be an important factor governing treatment response. Riva-Posse et al61 found that clinical response was seen when the electrodes stimulated 3 specific white matter bundles. Interestingly, nonresponders were converted to responders simply by changing the position of the electrodes to include these white matter tracts.61

        Adverse effects. The most common adverse effects noted during studies of DBS include pain at the site of implantation and wound infection. Other adverse effects include lead fracture, transient dysphagia, and other hardware-related problems.49

         

         

        Sorting out the evidence

        In the absence of head-to-head trials, it is difficult to establish a hierarchal algorithm for use of the 4 neuromodulatory treatments discussed in the article. If we were to base our decision solely on the current literature, ECT by far has the most evidence and highest remission rates.11 We can reduce the risk of cognitive deficits by using twice-weekly instead of thrice-weekly ECT, or by using unilateral instead of bilateral ECT.12 Another strategy for reducing adverse effects associated with long-term maintenance ECT is by using it in combination with VNS. ECT and VNS can be used safely concomitantly; ECT can be used to treat acutely worsening depression, and VNS for maintaining the antidepressant effect.62

        Aside from ECT, rTMS is the only other treatment that has evidence from RCTs. Although the remission rates are not as high as ECT, its preferable adverse effects profile, noninvasive nature, and comparative low cost (compared with surgical procedures) make it a favorable choice. The Canadian Network for Mood and Anxiety Treatment guidelines suggest rTMS as the first-line treatment for patients who do not respond to pharmacologic treatments.63 ECT can be considered second-line treatment unless the patient has acute suicidal ideation, catatonia, psychotic features, greater treatment resistance, or physical deterioration, in which case ECT should be tried before TMS.63

        Among the invasive options, VNS has more evidence and is FDA-approved for TRD. However, DBS has shown great promise in early studies, with remission rates as high as 35%.56 DBS has the advantage of being reversible, and the amount of stimulation can be adjusted easily. Despite early promise, more research is needed before DBS can be widely used in clinical settings.

        Bottom Line

        When considering neuromodulatory treatments for patients with TRD, current evidence suggests electroconvulsive therapy and repetitive transcranial magnetic stimulation are preferable options. Vagus nerve stimulation and deep brain stimulation have also shown promise.

        Related Resource

        • Bewernick B, Schlaepfer TE. Update on neuromodulation for treatment-resistant depression. 2015;4. doi: 10.12688/f1000research.6633.1.

        Drug Brand Names

        Lithium Eskalith, Lithobid
        Remifentanil Ultiva

        The emergence of treatment-resistant depression (TRD) poses a great clinical and public health challenge. There is no clear consensus on criteria to define TRD. The criteria range from failure to respond to 4 weeks of a single antidepressant to failure to respond to a single trial of electroconvulsive therapy (ECT).1

        Neuromodulatory treatments for depression involve electrical stimulation of the brain through invasive or noninvasive methods. In this article, we discuss criteria for defining TRD, and compare the advantages and disadvantages of 4 neuromodulatory treatment options—ECT, vagus nerve stimulation (VNS), repetitive transcranial magnetic stimulation (rTMS), and deep brain stimulation (DBS)—for patients with depression who fail to respond to appropriate pharmacologic interventions (Table 1). Most of the studies we discuss selected patients who had severe depression and had not responded to numerous treatment trials.

        Defining treatment resistance

        Thase and Rush2 suggested progressive stages for categorizing TRD, ranging from Stage I (failure of at least 1 adequate trial of antidepressants) to Stage V (failure of adequate treatment with 2 selective serotonin reuptake inhibitors [SSRIs], a tricyclic antidepressant, a monoamine oxidase inhibitor, and a course of bilateral ECT). The Massachusetts General Hospital Staging Model suggested a quantitative scale to help characterize the degree of treatment resistance in which a higher score corresponds to a higher level of resistance.3 For every failed 6-week trial with adequate dose of an antidepressant, the patient is given a score of 1. The patient receives an extra .5 point for failure to respond to optimization of the dosage and augmentation with another medication. The patient also is given 3 points for failure to respond to ECT. Souery et al4,5 proposed a model in which they defined TRD as a failure to respond after ≥1 adequate antidepressant trials of ≥12 weeks.

         

        Treatment resistance often is the result of inadequate treatment of depressive symptoms. Inadequate treatment includes an inadequate dose of antidepressants and/or an inadequate duration of treatment. Treatment of depression also is often complicated by medical (cardiovascular, neurologic, endocrine disorders) and psychiatric (substance abuse disorders, personality disorders) comorbidities (Table 2). Patients with such comorbidities are at increased risk of mortality, and have lower response rates and increased morbidity.6

        Electroconvulsive therapy

        ECT involves the application of electric current to induce a self-limiting seizure. It affects multiple brain functions to produce its antidepressant effects. Patients with depression have a reduced concentration of γ-aminobutyric acid (GABA) in their plasma, CSF, and cortex. ECT increases GABAergic transmission in cortical circuits as demonstrated by increased levels of GABA in the occipital cortex, which may be responsible for ECT’s antidepressant effects.7 Sensitization of the 5-HT1A receptors and increased dopamine receptor binding in the striatum also have been associated with the antidepressant action of ECT.8 The antidepressant effects of ECT also can be attributed to increased neuroplasticity, as evidenced by increased neuro­trophic factors and cell proliferation in animal models.9 Dysfunction of the HPA axis has long been associated with depressive disorders; ECT improves this dysfunction, as evidenced by normalization of the dexamethasone suppression test in patients who receive ECT.7

        The results of neuroimaging studies exploring the effects of ECT vary widely based on the specific neuroimaging method, population, and statistical methods used to assess the changes. Some of the most consistent findings include reduced glucose metabolism in the frontal brain regions; reduced glucose metabolism in the hippocampus and medial temporal lobes; and reduction in functional connectivity in the anterior cingulate, parietal, medical frontal, and dorsolateral prefrontal cortex (DLPFC).10

        Randomized control trials (RCTs) have established the superiority of ECT over pharmacotherapy and sham ECT. Compared with other neuromodulatory treatments, ECT has higher remission rates. On average, the remission rate among patients receiving ECT whose depression did not respond to pharmacotherapy is approximately 48%; this increases to 64.9% among patients who previously had responded to a medication.11

         

         

        Some earlier trials found bilateral ECT to be more effective than unilateral ECT.12 Recent studies suggest that high-dose unilateral ECT (6 times the seizure threshold) is as effective as bilateral ECT.13 Studies have shown no significant differences in efficacy or treatment outcomes between twice- and thrice-weekly ECT regimens. Some studies suggest that twice-weekly ECT may be associated with a lower risk of short-term cognitive impairment compared with thrice-weekly ECT.14

        In highly refractory cases, the effects of ECT can be augmented by using pre-treatment strategies such as hyperventilation, which may increase the duration of the seizure, and remifentanil, which helps reduce the anticonvulsant effect of agents used for anesthesia.15 Advanced age, psychotic features, resistance to pharmacotherapy, and comorbid personality disorders predict poor response to ECT.16

        Adverse effects. Concerns about cognitive deficits secondary to ECT may curtail its use. Retrograde and anterograde amnesia are the most common deficits observed acutely after ECT.12 Other commonly affected cognitive functions include processing speed, attention/working memory, verbal and visual episodic memory, spatial problem solving, and executive functioning. The specific patterns of these deficits (in terms of duration and severity) vary between studies. In general, high-dose, thrice-weekly ECT and bilateral ECT are associated with greater cognitive deficits, whereas twice-weekly ECT and unilateral ECT are associated with a lower risk of cognitive adverse effects.12 A recent meta-analysis by Semkovska and McLoughlin17 found that most cognitive deficits seen after ECT are limited to the first 3 days after treatment. The authors of this meta-analysis concluded that these impairments improve over time and approach baseline 2 weeks after treatment. In fact, some of these impairments (processing speed, working memory, anterograde memory, and some aspects of executive function) improved beyond baseline after 15 days of treatment.17 The need for anesthesia and associated potential adverse effects also are a cause of concern with ECT.

        Combining ECT with medication. Several patient-specific factors, including medication regimen and comorbid medical conditions, need to be considered before using ECT in combination with pharmacotherapy. Although most antipsychotics are safe to use with ECT, concomitant use of agents with higher antihistaminic properties may increase the risk of delirium. The risk of delirium also is increased with the use of anticonvulsants and mood stabilizers (eg, lithium) because these agents increase the seizure threshold. The potential for drug interactions may affect the choice of the anesthetic agents. Also, SSRIs and serotonin-norepinephrine reuptake inhibitors can increase the duration of induced seizures.18

        Vagus nerve stimulation

        VNS, in which an implanted device stimulates the vagus nerve with electrical impulses, initially was used to reduce the frequency of seizures in patients with epilepsy and treatment-resistant partial onset seizures.19 VNS was FDA-approved for TRD in July 2005.20 One VNS system, the NCP System, consists of an implantable, multi-programmable generator, known as a pulse generator, that is subcutaneously placed in the anterior chest wall during an outpatient surgical procedure. Separate bipolar nerve-stimulating electrodes are surgically wrapped around the left cervical vagus nerve, and then connected to the generator via a tunneling procedure. A telemetric wand is subsequently linked to a portable computer and used to adjust stimulation parameters.21,22

         

         

        Support for using VNS for TRD came from a multitude of investigations and observations. Harden et al23 and Elger et al24 prospectively evaluated epileptic patients with standard depression symptom severity rating scales. They found that VNS was associated with statistically significant improvements in mood that were not related to reductions in seizures.23,24

        The mechanism of action of VNS is not clear. Earlier researchers had found evidence that VNS affected brain regions associated with norepinephrine25 and serotonin systems26; both of these neuro­transmitters have been implicated in the pathophysiology of depression. Positron emission tomography studies conducted during VNS treatment of epilepsy showed metabolic changes in cortical and subcortical areas of the brain, including the amygdala, hippocampus, and cingulate gyrus, all structures implicated in the pathophysiology of mood disorders.27

        Most studies conducted to evaluate the efficacy of VNS have been observational, looking at depression ratings before and after treatment with VNS. The short-term studies measured the difference in depression rating scales at baseline and after 10 weeks of treatment. In most of these studies, treatment with VNS resulted in a statistically significant drop in depression rating scales scores, such as on the Hamilton Depression Rating Scale (HAM-D). Based on the study design and number of study participants, response rates have varied from 13%28 to 40%,29 whereas remission rates have varied from 15.3%30 to 28%.31 More than one-half of the reduction in symptoms occurred after 6 weeks of treatment.30 In longer-term follow-up studies, the antidepressant effect generally was sustained over time. Response rates remained essentially unchanged, but the remission rates increased to approximately 29%.29 Only 1 RCT has compared patients with controls; it found no significant differences in the response or remission rates between active VNS and sham VNS.32 In this study, all patients had VNS implanted, but in the control group, the VNS was never turned on.32 In a meta-analysis conducted by Martin and Martín-Sánchez,33 31.8% (95% confidence interval [CI], 23.2% to 41.8%; P < .001) of patients treated with VNS had a significant reduction in HAM-D scores. The response rate in patients with TRD ranged from 27% to 37% and the remission rate was approximately 13%. In studies that followed patients over longer periods, both the remission and response rates increased over time.34

        Recent evidence suggests that the effectiveness of VNS may depend on the stimulation level. A multi-center double-blind study randomized patients to receive either a low (0.25 mA current, 130-millisecond pulse width), medium (0.5e1.0 mA, 250 millisecond), or high (1.25e1.5 mA, 250 millisecond) dose of VNS.35 Although all dose levels were associated with improvement in symptoms, a statistically significant durability in response was associated with the medium- and high-dose treatments.

        Adverse effects. VNS has no major adverse effects on cognitive functioning, and some studies have found improvement in executive functioning that corresponded to improvement in depressive symptoms.30 VNS also may result in improved sleep patterns as evidenced by EEG changes.31 The most commonly reported adverse effects include pain in the incision site, hoarseness of voice, throat pain, and neck pain.36

         

         

        Repetitive transcranial magnetic stimulation

        rTMS is a noninvasive technique that uses high-intensity magnetic impulses to stimulate cortical neurons. A magnetic field is produced when current passes through a coil, which in turn causes electrical stimulation in the cortical neurons that results in transient changes in the excitability of the cortical neurons.37 Although many stimulation parameters exist for TMS, high-frequency stimulation to the left prefrontal cortex (HFL-rTMS) and low-frequency stimulation to the right prefrontal cortex (LFR-rTMS) have been shown most efficacious for treating depression.38 High-frequency (5 Hz to 20 Hz) stimulation using rTMS increases cortical neuron excitability, whereas low-frequency (approximately 1 Hz) is associated with reduced cortical neuron excitability.39 The choice of targeting the DLPFC stems from a large body of functional neuroimaging studies that have shown reduction in activity/blood flow in the left DLPFC and abnormal activity/blood flow in the right DLPFC.40

        There is no dearth of RCTs evaluating the efficacy of rTMS vs sham rTMS (where no magnetic stimulation was provided). In a meta-analysis of 8 RCTs, low-frequency rTMS applied to the right DLPFC was associated with a remission rate of approximately 34.6%, compared with a 9.7% remission rate with sham rTMS.41 A response rate of approximately 38.2% was observed with HFL-rTMS, compared with a response rate of 15.1% for sham rTMS.41

        Gaynes et al42 conducted a meta-analysis to determine the efficacy of rTMS in TRD. They found that for patients with TRD, rTMs produced a response rate of 29% and a remission rate of 30%. In long-term, naturalistic, observational studies, the response rates and remission rates were much higher (58% and 37.1%, respectively).43 Over a 1-year follow-up, almost two-thirds of patients continued to meet criteria for response to treatment.44 Trials comparing HFL-rTMS and LFR-rTMS have found no significant differences in efficacy.45

        Advanced age, psychotic symptoms, and a longer duration of the current depressive episode predict poor response to rTMS. Also, imaging studies have shown that a lower metabolism in cerebellar, temporal, anterior cingulate, and occipital parts of the brain correlate with better response to HFL-rTMS.46,47

        Adverse effects. The major adverse effect associated with rTMS is the risk of inducing seizures, which is more commonly associated with high-frequency rTMS. Other common adverse effects include headache, facial muscle twitching, and tinnitus.37

         

         

        Deep brain stimulation

        DBS is an invasive stereotactic surgical procedure. It involves unilateral or bilateral placement of electrodes at neuroanatomical locations to deliver continuous stimulation from a subcutaneously implanted pulse generator.48 In the past, destructive surgical procedures were used to treat intractable depression. Surgeries such as anterior cingulotomy, anterior capsulotomy, subcaudate tractotomy, and limbic leucotomy have been shown to effectively reduce depressive symptoms.49 The advantages of DBS over destructive procedures include the fact that DBS is reversible and that the stimulation levels can easily be adjusted, and the treatment can easily be stopped or restarted.

        There is no consensus on the optimal anatomic locations for the electrode implantation in DBS. Electrodes have been implanted in the subcallosal cingulate gyrus, inferior thalamic peduncle, ventral capsule/ventral striatum, superolateral branch of the medial forebrain bundle (MFB), and nucleus accumbens.

        The choice of anatomic locations stems from the large body of neuroimaging literature characterizing functional changes associated with acute depression and response to treatment. The electrode placement targets “nodes” that form an integral part of the affected neural circuits that are responsible for regulating depressive symptoms.50 Increased metabolic activity and blood flow to the subgenual cingulate gyrus and reduction in the blood flow to the DLPFC and the striatum have been associated with active depressed states. Response to antidepressant treatment has been associated with reversal of these findings.51 Functional magnetic resonance imaging studies have consistently shown increased activity in the amygdala in response to negative stimuli among patients with depression.

        Regardless of the site of electrode placement, studies have reported symptomatic improvement among patients with depression who are treated with DBS. In 2 case reports, the electrode was implanted in the inferior thalamic peduncle.52,53 Each study had 1 participant, and each patient remitted.52,53

        Placement of the electrodes in the nucleus accumbens resulted in a response rate of 45% in 1 study,54 whereas in a different study, all patients reported improvement in anhedonia.55 A response rate of 71% and a remission rate of 35% were observed in a study in which the electrode was implanted in the ventral capsule/ventral striatum area.56

         

         

        Berlim et al57 published a systematic review and exploratory meta-analysis of studies in which the electrode had been implanted in the subgenual cingulate cortex. At 12 months, the response rate was 39.9% (95% CI, 28.4% to 52.8%), and 26.3% (95% CI, 13% to 45.9%) of patients achieved remission. The most significant drop in depression scores was observed 3 to 6 months after the surgery. No significant change in scores was observed between 6 to 12 months after surgery.57

        The MFB, specifically the superolateral branch, is emerging as an exciting new target for electrode placement in DBS. Schlaepfer et al58 studied the effects of electrodes implanted bilaterally in the superolateral branch of the MFB. They observed an almost 50% reduction in symptoms by Day 7, and at the last follow-up visit (12 to 33 weeks) 4 of the 6 patients had achieved remission.58 In a recent systematic review, Gálvez et al59 found most studies had high response/remission rates without any significant adverse effects. In a recent study of DBS targeting the MFB, 3 of 4 patients had a >50% reduction in Montgomery-Åsberg Depression Rating Scale scores at the end of first week. Although 1 patient withdrew, 2 of the other 3 patients continued to report a >80% reduction in depressive symptoms, even at Week 26.60

        Accurate localization of target areas (white matter tracts) and subsequent electrode placement might be an important factor governing treatment response. Riva-Posse et al61 found that clinical response was seen when the electrodes stimulated 3 specific white matter bundles. Interestingly, nonresponders were converted to responders simply by changing the position of the electrodes to include these white matter tracts.61

        Adverse effects. The most common adverse effects noted during studies of DBS include pain at the site of implantation and wound infection. Other adverse effects include lead fracture, transient dysphagia, and other hardware-related problems.49

         

         

        Sorting out the evidence

        In the absence of head-to-head trials, it is difficult to establish a hierarchal algorithm for use of the 4 neuromodulatory treatments discussed in the article. If we were to base our decision solely on the current literature, ECT by far has the most evidence and highest remission rates.11 We can reduce the risk of cognitive deficits by using twice-weekly instead of thrice-weekly ECT, or by using unilateral instead of bilateral ECT.12 Another strategy for reducing adverse effects associated with long-term maintenance ECT is by using it in combination with VNS. ECT and VNS can be used safely concomitantly; ECT can be used to treat acutely worsening depression, and VNS for maintaining the antidepressant effect.62

        Aside from ECT, rTMS is the only other treatment that has evidence from RCTs. Although the remission rates are not as high as ECT, its preferable adverse effects profile, noninvasive nature, and comparative low cost (compared with surgical procedures) make it a favorable choice. The Canadian Network for Mood and Anxiety Treatment guidelines suggest rTMS as the first-line treatment for patients who do not respond to pharmacologic treatments.63 ECT can be considered second-line treatment unless the patient has acute suicidal ideation, catatonia, psychotic features, greater treatment resistance, or physical deterioration, in which case ECT should be tried before TMS.63

        Among the invasive options, VNS has more evidence and is FDA-approved for TRD. However, DBS has shown great promise in early studies, with remission rates as high as 35%.56 DBS has the advantage of being reversible, and the amount of stimulation can be adjusted easily. Despite early promise, more research is needed before DBS can be widely used in clinical settings.

        Bottom Line

        When considering neuromodulatory treatments for patients with TRD, current evidence suggests electroconvulsive therapy and repetitive transcranial magnetic stimulation are preferable options. Vagus nerve stimulation and deep brain stimulation have also shown promise.

        Related Resource

        • Bewernick B, Schlaepfer TE. Update on neuromodulation for treatment-resistant depression. 2015;4. doi: 10.12688/f1000research.6633.1.

        Drug Brand Names

        Lithium Eskalith, Lithobid
        Remifentanil Ultiva

        References

        1. Berlim MT, Turecki G. What is the meaning of treatment resistant/refractory major depression (TRD)? A systematic review of current randomized trials. Eur Neuropsychopharmacol. 2007;17(11):696-707.
        2. Thase ME, Rush AJ. When at first you don’t succeed: sequential strategies for antidepressant nonresponders. J Clin Psychiatry. 1997;58(suppl 13):23-29.
        3. Petersen T, Papakostas GI, Posternak MA, et al. Empirical testing of two models for staging antidepressant treatment resistance. J Clin Psychopharmacol. 2005;25(4):336-341.
        4. Souery D, Papakostas GI, Trivedi MH. Treatment-resistant depression. J Clin Psychiatry. 2006;67(suppl 6):16-22.
        5. Souery D, Amsterdam J, de Montigny C, et al. Treatment resistant depression: methodological overview and operational criteria. Eur Neuropsychopharmacol. 1999;9(1-2):83-91.
        6. Evans DL, Charney DS. Mood disorders and medical illness: a major public health problem. Biol. Psychiatry. 2003;54(3):177-180.
        7. Sanacora G, Mason GF, Rothman DL, et al. Increased cortical GABA concentrations in depressed patients receiving ECT. Am J Psychiatry. 2003;160(3):577-579.
        8. Merkl A, Heuser I, Bajbouj M. Antidepressant electroconvulsive therapy: mechanism of action, recent advances and limitations. Exp Neurol. 2009;219(1):20-26.
        9. Perera TD, Coplan JD, Lisanby SH, et al. Antidepressant-induced neurogenesis in the hippocampus of adult nonhuman primates. J. Neurosci. 2007;27(18):4894-4901.
        10. Abbott CC, Gallegos P, Rediske N et al. A review of longitudinal electroconvulsive therapy: neuroimaging investigations. J Geriatr Psychiatry Neurol. 2014;27(1):33-46.
        11. Heijnen WT, Birkenhäger TK, Wierdsma AI, et al. Antidepressant pharmacotherapy failure and response to subsequent electroconvulsive therapy: a meta-analysis. J Clin Psychopharmacol. 2010;30(5):616-619.
        12. UK ECT Review Group. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet. 2003;361(9360):799-808.
        13. Semkovska M, Landau S, Dunne R et al. Bitemporal versus high-dose unilateral twice-weekly electroconvulsive therapy for depression (EFFECT-Dep): a pragmatic, randomized, non-inferiority trial. Am J Psychiatry. 2016;173(4):408-417.
        14. Charlson F, Siskind D, Doi SA, et al. ECT efficacy and treatment course: a systematic review and meta-analysis of twice vs thrice weekly schedules. J Affect Disord. 2012;138(1-2):1-8.
        15. Loo CK, Kaill A, Paton P, et al. The difficult-to-treat electroconvulsive therapy patient—strategies for augmenting outcomes. J Affect Disord. 2010;124(3):219-227.
        16. de Vreede IM, Burger H, van Vliet IM. Prediction of response to ECT with routinely collected data in major depression. J Affect Disord. 2005;86(2-3):323-327.
        17. Semkovska M, McLoughlin DM. Objective cognitive performance associated with electroconvulsive therapy for depression: a systematic review and meta-analysis. Biol Psychiatry. 2010;68(6):568-577.
        18. Baghai TC, Marcuse A, Brosch M, et al. The influence of concomitant antidepressant medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J Biol Psychiatry. 2006;7(2):82-90.
        19. Ben-Menachem E, Mañon-Espaillat R, Ristanovic R, et al. Vagus nerve stimulation for treatment of partial seizures: 1. A controlled study of effect on seizures. First International Vagus Nerve Stimulation Study Group. Epilepsia. 1994;35(3):616-626.
        20. Nemeroff CB, Mayberg HS, Krahl SE, et al. VNS therapy in treatment-resistant depression: clinical evidence and putative neurobiological mechanisms. Neuropsychopharmacology. 2006;31(7):1345-1355.
        21. Matthews K, Eljamel MS. Vagus nerve stimulation and refractory depression: please can you switch me on doctor? Br J Psychiatry. 2003;183:181-183.
        22. George MS, Rush AJ, Sackeim HA, et al. Vagus nerve stimulation (VNS): utility in neuropsychiatric disorders. Int J Neuropsychopharmacol. 2003;6(1):73-83.
        23. Harden CL, Pulver MC, Ravdin LD, et al. A pilot study of mood in epilepsy patients treated with vagus nerve stimulation. Epilepsy Behav. 2000;1(2):93-99.
        24. Elger G, Hoppe C, Falkai P, et al. Vagus nerve stimulation is associated with mood improvements in epilepsy patients. Epilepsy Res. 2000;42(2-3):203-210.
        25. Krahl SE, Clark KB, Smith DC, et al. Locus coeruleus lesions suppress the seizure-attenuating effects of vagus nerve stimulation. Epilepsia. 1998;39(7):709-714.
        26. Ben-Menachem E, Hamberger A, Hedner T, et al. Effects of vagus nerve stimulation on amino acids and other metabolites in the CSF of patients with partial seizures. Epilepsy Res. 1995;20(3):221-227.
        27. Henry TR, Bakay RA, Votaw JR, et al. Brain blood flow alterations induced by therapeutic vagus nerve stimulation in partial epilepsy: I. Acute effects at high and low levels of stimulation. Epilepsia. 1998;39(9):983-990.
        28. O’Keane V, Dinan TG, Scott L, et al. Changes in hypothalamic-pituitary-adrenal axis measures after vagus nerve stimulation therapy in chronic depression. Biol Psychiatry. 2005;58(12):963-968.
        29. Rush AJ, George MS, Sackeim HA, et al. Vagus nerve stimulation (VNS) for treatment-resistant depressions: a multicenter study. Biol Psychiatry. 2000;47(4):276-286.
        30. Sackeim HA, Rush AJ, George MS, et al. Vagus nerve stimulation (VNS) for treatment-resistant depression: efficacy, side effects, and predictors of outcome. Neuropsychopharmacology. 2001;25(5):713-728.
        31. Armitage R, Husain M, Hoffmann R, et al. The effects of vagus nerve stimulation on sleep EEG in depression: a preliminary report. J Psychosom Res. 2003;54(5):475-482.
        32. Rush AJ, Marangell LB, Sackeim HA, et al. Vagus nerve stimulation for treatment-resistant depression: a randomized, controlled acute phase trial. Biol Psychiatry. 2005;58(5):347-354.
        33. Martin JL, Martín-Sánchez E. Systematic review and meta-analysis of vagus nerve stimulation in the treatment of depression: variable results based on study designs. Eur Psychiatry. 2012;27(3):147-155.
        34. Shah A, Carreno FR, Frazer A. Therapeutic modalities for treatment resistant depression: focus on vagal nerve stimulation and ketamine. Clin Psychopharmacol Neurosci. 2014;12(2):83-93.
        35. Aaronson ST, Carpenter LL, Conway CR, et al. Vagus nerve stimulation therapy randomized to different amounts of electrical charge for treatment-resistant depression: acute and chronic effects. Brain Stimul. 2013;6(4):631-640.
        36. Daban C, Martinez-Aran A, Cruz N, et al. Safety and efficacy of vagus nerve stimulation in treatment-resistant depression. A systematic review. J Affect Disord. 2008;110(1-2):1-15.
        37. Eitan R, Lerer B. Nonpharmacological, somatic treatments of depression: electroconvulsive therapy and novel brain stimulation modalities. Dialogues Clin Neurosci. 2006;8(2):241-258.
        38. Lam RW, Chan P, Wilkins-Ho M, et al. Repetitive transcranial magnetic stimulation for treatment-resistant depression: a systematic review and metaanalysis. Can J Psychiatry. 2008;53(9):621-631.
        39. Fitzgerald PB, Fountain S, Daskalakis ZJ. A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition. Clin Neurophysiol. 2006;117(12):2584-2596.
        40. Fitzgerald PB, Oxley TJ, Laird AR, et al. An analysis of functional neuroimaging studies of dorsolateral prefrontal cortical activity in depression. Psychiatry Res. 2006;148(1):33-45.
        41. Berlim MT, Van den Eynde F, Daskalakis ZJ. Clinically meaningful efficacy and acceptability of low-frequency repetitive transcranial magnetic stimulation (rTMS) for treating primary major depression: a meta-analysis of randomized, double-blind and sham-controlled trials. Neuropsychopharmacology. 2013;38(4):543-551.
        42. Gaynes BN, Lloyd SW, Lux L, et al. Repetitive transcranial magnetic stimulation for treatment-resistant depression. J Clin Psychiatry. 2014;75(5):477-489; quiz 489.
        43. Carpenter LL, Janicak PG, Aaronson ST, et al. Transcranial magnetic stimulation (TMS) for major depression: a multisite, naturalistic, observational study of acute treatment outcomes in clinical practice. Depress Anxiety. 2012;29(7):587-596.
        44. Dunner DL, Aaronson ST, Sackeim HA, et al. A multisite, naturalistic, observational study of transcranial magnetic stimulation for patients with pharmacoresistant major depressive disorder. J Clin Psychiatry. 2014;75(12):1394-1401.
        45. Fitzgerald PB, Hoy K, Daskalakis ZJ, et al. A randomized trial of the anti-depressant effects of low- and high-frequency transcranial magnetic stimulation in treatment-resistant depression. Depress Anxiety. 2009;26(3):229-234.
        46. Dumas R, Padovani R, Richieri R, et al. Repetitive transcranial magnetic stimulation in major depression: response factor [in French]. Encephale. 2012;38(4):360-368.
        47. Fregni F, Marcolin MA, Myczkowski M, et al. Predictors of antidepressant response in clinical trials of transcranial magnetic stimulation. Int. J. Neuropsychopharmacol. 2006;9(6):641-654.
        48. Kennedy SH, Giacobbe P, Rizvi SJ, et al. Deep brain stimulation for treatment-resistant depression: follow-up after 3 to 6 years. Am J Psychiatry. 2011;168(5):502-510.
        49. Taghva AS, Malone DA, Rezai AR. Deep brain stimulation for treatment-resistant depression. World Neurosurg. 2013;80(3-4):S27.e17-S27.e24.
        50. Mayberg HS. Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algorithms for diagnosis and optimised treatment. Br Med Bull. 2003;65:193-207.
        51. Mayberg HS, Liotti M, Brannan SK, et al. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am J Psychiatry. 1999;156(5):675-682.
        52. Jiménez F, Velasco F, Salín-Pascual R, et al. Neuromodulation of the inferior thalamic peduncle for major depression and obsessive compulsive disorder. Acta Neurochir Suppl. 2007;97(pt 2):393-398.
        53. Jiménez F, Velasco F, Salin-Pascual R, et al. A patient with a resistant major depression disorder treated with deep brain stimulation in the inferior thalamic peduncle. Neurosurgery. 2005;57(3):585-593; discussion 585-593.
        54. Bewernick BH, Hurlemann R, Matusch A, et al. Nucleus accumbens deep brain stimulation decreases ratings of depression and anxiety in treatment-resistant depression. Biol Psychiatry. 2010;67(2):110-116.
        55. Schlaepfer TE, Bewernick BH, Kayser S, et al. Deep brain stimulation of the human reward system for major depression—rationale, outcomes and outlook. Neuropsychopharmacology. 2014;39(6):1303-1314.
        56. Malone DA Jr, Dougherty DD, Rezai AR, et al. Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. Biol Psychiatry. 2009;65(4):267-275.
        57. Berlim MT, McGirr A, Van den Eynde F, et al. Effectiveness and acceptability of deep brain stimulation (DBS) of the subgenual cingulate cortex for treatment-resistant depression: a systematic review and exploratory meta-analysis. J Affect Disord. 2014;159:31-38.
        58. Schlaepfer TE, Bewernick BH, Kayser S, et al. Rapid effects of deep brain stimulation for treatment-resistant major depression. Biol Psychiatry. 2013;73(12):1204-1212.
        59. Gálvez JF, Keser Z, Mwangi B, et al. The medial forebrain bundle as a deep brain stimulation target for treatment resistant depression: a review of published data. Prog Neuropsychopharmacol Biol Psychiatry. 2015;58:59-70.
        60. Fenoy AJ, Schulz P, Selvaraj. Deep brain stimulation of the medial forebrain bundle: distinctive responses in resistant depression. J Affect Disord. 2016;203:143-151.
        61. Riva-Posse P, Choi KS, Holtzheimer PE, et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol Psychiatry. 2014;76(12):963-969.
        62. Burke MJ, Husain MM. Concomitant use of vagus nerve stimulation and electroconvulsive therapy for treatment-resistant depression. J ECT. 2006;22(3):218-222.
        63. Milev R V, Giacobbe P, Kennedy SH, et al; CANMAT Depression Work Group. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: section 4. Neurostimulation treatments. Can J Psychiatry. 2016;61:561-575.

        References

        1. Berlim MT, Turecki G. What is the meaning of treatment resistant/refractory major depression (TRD)? A systematic review of current randomized trials. Eur Neuropsychopharmacol. 2007;17(11):696-707.
        2. Thase ME, Rush AJ. When at first you don’t succeed: sequential strategies for antidepressant nonresponders. J Clin Psychiatry. 1997;58(suppl 13):23-29.
        3. Petersen T, Papakostas GI, Posternak MA, et al. Empirical testing of two models for staging antidepressant treatment resistance. J Clin Psychopharmacol. 2005;25(4):336-341.
        4. Souery D, Papakostas GI, Trivedi MH. Treatment-resistant depression. J Clin Psychiatry. 2006;67(suppl 6):16-22.
        5. Souery D, Amsterdam J, de Montigny C, et al. Treatment resistant depression: methodological overview and operational criteria. Eur Neuropsychopharmacol. 1999;9(1-2):83-91.
        6. Evans DL, Charney DS. Mood disorders and medical illness: a major public health problem. Biol. Psychiatry. 2003;54(3):177-180.
        7. Sanacora G, Mason GF, Rothman DL, et al. Increased cortical GABA concentrations in depressed patients receiving ECT. Am J Psychiatry. 2003;160(3):577-579.
        8. Merkl A, Heuser I, Bajbouj M. Antidepressant electroconvulsive therapy: mechanism of action, recent advances and limitations. Exp Neurol. 2009;219(1):20-26.
        9. Perera TD, Coplan JD, Lisanby SH, et al. Antidepressant-induced neurogenesis in the hippocampus of adult nonhuman primates. J. Neurosci. 2007;27(18):4894-4901.
        10. Abbott CC, Gallegos P, Rediske N et al. A review of longitudinal electroconvulsive therapy: neuroimaging investigations. J Geriatr Psychiatry Neurol. 2014;27(1):33-46.
        11. Heijnen WT, Birkenhäger TK, Wierdsma AI, et al. Antidepressant pharmacotherapy failure and response to subsequent electroconvulsive therapy: a meta-analysis. J Clin Psychopharmacol. 2010;30(5):616-619.
        12. UK ECT Review Group. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet. 2003;361(9360):799-808.
        13. Semkovska M, Landau S, Dunne R et al. Bitemporal versus high-dose unilateral twice-weekly electroconvulsive therapy for depression (EFFECT-Dep): a pragmatic, randomized, non-inferiority trial. Am J Psychiatry. 2016;173(4):408-417.
        14. Charlson F, Siskind D, Doi SA, et al. ECT efficacy and treatment course: a systematic review and meta-analysis of twice vs thrice weekly schedules. J Affect Disord. 2012;138(1-2):1-8.
        15. Loo CK, Kaill A, Paton P, et al. The difficult-to-treat electroconvulsive therapy patient—strategies for augmenting outcomes. J Affect Disord. 2010;124(3):219-227.
        16. de Vreede IM, Burger H, van Vliet IM. Prediction of response to ECT with routinely collected data in major depression. J Affect Disord. 2005;86(2-3):323-327.
        17. Semkovska M, McLoughlin DM. Objective cognitive performance associated with electroconvulsive therapy for depression: a systematic review and meta-analysis. Biol Psychiatry. 2010;68(6):568-577.
        18. Baghai TC, Marcuse A, Brosch M, et al. The influence of concomitant antidepressant medication on safety, tolerability and clinical effectiveness of electroconvulsive therapy. World J Biol Psychiatry. 2006;7(2):82-90.
        19. Ben-Menachem E, Mañon-Espaillat R, Ristanovic R, et al. Vagus nerve stimulation for treatment of partial seizures: 1. A controlled study of effect on seizures. First International Vagus Nerve Stimulation Study Group. Epilepsia. 1994;35(3):616-626.
        20. Nemeroff CB, Mayberg HS, Krahl SE, et al. VNS therapy in treatment-resistant depression: clinical evidence and putative neurobiological mechanisms. Neuropsychopharmacology. 2006;31(7):1345-1355.
        21. Matthews K, Eljamel MS. Vagus nerve stimulation and refractory depression: please can you switch me on doctor? Br J Psychiatry. 2003;183:181-183.
        22. George MS, Rush AJ, Sackeim HA, et al. Vagus nerve stimulation (VNS): utility in neuropsychiatric disorders. Int J Neuropsychopharmacol. 2003;6(1):73-83.
        23. Harden CL, Pulver MC, Ravdin LD, et al. A pilot study of mood in epilepsy patients treated with vagus nerve stimulation. Epilepsy Behav. 2000;1(2):93-99.
        24. Elger G, Hoppe C, Falkai P, et al. Vagus nerve stimulation is associated with mood improvements in epilepsy patients. Epilepsy Res. 2000;42(2-3):203-210.
        25. Krahl SE, Clark KB, Smith DC, et al. Locus coeruleus lesions suppress the seizure-attenuating effects of vagus nerve stimulation. Epilepsia. 1998;39(7):709-714.
        26. Ben-Menachem E, Hamberger A, Hedner T, et al. Effects of vagus nerve stimulation on amino acids and other metabolites in the CSF of patients with partial seizures. Epilepsy Res. 1995;20(3):221-227.
        27. Henry TR, Bakay RA, Votaw JR, et al. Brain blood flow alterations induced by therapeutic vagus nerve stimulation in partial epilepsy: I. Acute effects at high and low levels of stimulation. Epilepsia. 1998;39(9):983-990.
        28. O’Keane V, Dinan TG, Scott L, et al. Changes in hypothalamic-pituitary-adrenal axis measures after vagus nerve stimulation therapy in chronic depression. Biol Psychiatry. 2005;58(12):963-968.
        29. Rush AJ, George MS, Sackeim HA, et al. Vagus nerve stimulation (VNS) for treatment-resistant depressions: a multicenter study. Biol Psychiatry. 2000;47(4):276-286.
        30. Sackeim HA, Rush AJ, George MS, et al. Vagus nerve stimulation (VNS) for treatment-resistant depression: efficacy, side effects, and predictors of outcome. Neuropsychopharmacology. 2001;25(5):713-728.
        31. Armitage R, Husain M, Hoffmann R, et al. The effects of vagus nerve stimulation on sleep EEG in depression: a preliminary report. J Psychosom Res. 2003;54(5):475-482.
        32. Rush AJ, Marangell LB, Sackeim HA, et al. Vagus nerve stimulation for treatment-resistant depression: a randomized, controlled acute phase trial. Biol Psychiatry. 2005;58(5):347-354.
        33. Martin JL, Martín-Sánchez E. Systematic review and meta-analysis of vagus nerve stimulation in the treatment of depression: variable results based on study designs. Eur Psychiatry. 2012;27(3):147-155.
        34. Shah A, Carreno FR, Frazer A. Therapeutic modalities for treatment resistant depression: focus on vagal nerve stimulation and ketamine. Clin Psychopharmacol Neurosci. 2014;12(2):83-93.
        35. Aaronson ST, Carpenter LL, Conway CR, et al. Vagus nerve stimulation therapy randomized to different amounts of electrical charge for treatment-resistant depression: acute and chronic effects. Brain Stimul. 2013;6(4):631-640.
        36. Daban C, Martinez-Aran A, Cruz N, et al. Safety and efficacy of vagus nerve stimulation in treatment-resistant depression. A systematic review. J Affect Disord. 2008;110(1-2):1-15.
        37. Eitan R, Lerer B. Nonpharmacological, somatic treatments of depression: electroconvulsive therapy and novel brain stimulation modalities. Dialogues Clin Neurosci. 2006;8(2):241-258.
        38. Lam RW, Chan P, Wilkins-Ho M, et al. Repetitive transcranial magnetic stimulation for treatment-resistant depression: a systematic review and metaanalysis. Can J Psychiatry. 2008;53(9):621-631.
        39. Fitzgerald PB, Fountain S, Daskalakis ZJ. A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition. Clin Neurophysiol. 2006;117(12):2584-2596.
        40. Fitzgerald PB, Oxley TJ, Laird AR, et al. An analysis of functional neuroimaging studies of dorsolateral prefrontal cortical activity in depression. Psychiatry Res. 2006;148(1):33-45.
        41. Berlim MT, Van den Eynde F, Daskalakis ZJ. Clinically meaningful efficacy and acceptability of low-frequency repetitive transcranial magnetic stimulation (rTMS) for treating primary major depression: a meta-analysis of randomized, double-blind and sham-controlled trials. Neuropsychopharmacology. 2013;38(4):543-551.
        42. Gaynes BN, Lloyd SW, Lux L, et al. Repetitive transcranial magnetic stimulation for treatment-resistant depression. J Clin Psychiatry. 2014;75(5):477-489; quiz 489.
        43. Carpenter LL, Janicak PG, Aaronson ST, et al. Transcranial magnetic stimulation (TMS) for major depression: a multisite, naturalistic, observational study of acute treatment outcomes in clinical practice. Depress Anxiety. 2012;29(7):587-596.
        44. Dunner DL, Aaronson ST, Sackeim HA, et al. A multisite, naturalistic, observational study of transcranial magnetic stimulation for patients with pharmacoresistant major depressive disorder. J Clin Psychiatry. 2014;75(12):1394-1401.
        45. Fitzgerald PB, Hoy K, Daskalakis ZJ, et al. A randomized trial of the anti-depressant effects of low- and high-frequency transcranial magnetic stimulation in treatment-resistant depression. Depress Anxiety. 2009;26(3):229-234.
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