THE CASE

A 26-year-old Hispanic/African American woman presented to our clinic with a 2-month history of nausea and vomiting, along with dizziness. The nausea and vomiting persistently worsened, and she was only able to tolerate apples and berries. During this 2-month period, she lost 20 pounds and her symptoms progressed to include pruritus, ataxia, and mild hearing loss, with reoccurring episodes of falls.

THE DIAGNOSIS

On examination, she was found to be bradycardic with a heart rate of 47 beats/min, right- axis deviation, and inverted T waves in leads I, II, and augmented vector left. Her family history included the death of an aunt who was in her early 30s due to an unknown heart condition.

Echocardiogram identified mild mitral valve regurgitation with an ejection fraction of 55% to 60% (reference range: 55%-70%). Cardiology determined that her bradycardia was not the source of her symptoms. A neurologic exam identified 3+ hyperreflexia (indicating the reflex was increased), tandem gait instability, and left oculomotor dysfunction.

Brain magnetic resonance imaging (MRI) identified bilateral parietal white matter lesions where a demyelinating process could not be excluded (FIGURE 1A). The patient’s symptoms of nausea and vomiting continued, and she only tolerated peanuts and liquids. An MRI of the spine was negative.

Laboratory testing revealed that the patient was negative for human immunodeficiency virus (HIV), syphilis, Lyme disease, and lupus. Her thyroid-stimulating hormone level was 1.7 mIU/L (reference range: 0.4-4.2 mIU/L), and her vitamin B₁₂ level was 504 pg/mL (reference range: 160-950 pg/mL).

The patient’s lumbar puncture was negative for oligoclonal bands. The IgG synthesis rate/index cerebrospinal fluid (CSF) was –3.9, ruling out multiple sclerosis. Her CSF culture was negative, with a glucose level of 42 mg/dL (reference range: 70-110 mg/dL), colorless appearance, 1 white blood cell, and spinal albumin of 12.2 mg/dL (reference range: 8-42 mg/dL). The visual evoked potential was negative. The aquaporin-4 (AQP4) antibody was positive at 3.4 U/mL, and the myelin oligodendrocyte glycoprotein (MOG) antibody was positive.

Gastroenterology concluded a normal gastric accommodation and unremarkable computed tomography (CT) enterography. Moderate erosions were identified in the stomach with an erythematous gastropathy. The patient was placed on a proton pump inhibitor.

Continue to: Following the examination...

Following the examination and laboratory testing, the patient was admitted under our family medicine service for neuromyelitis optica (NMO) affecting the area postrema. NMO, also known as Devic’s disease, is an autoimmune disorder that affects the spinal cord and optic nerves. Autoantibodies against AQP4 are created in the periphery and are directed against astrocytes in the central nervous system. These antibodies bind to the foot processes of astrocytes, inducing complement-mediated cell damage and granulocyte infiltration.^1-5

Intravenous methylprednisolone was initiated at 250 mg every 6 hours for 3 days. A repeat brain MRI demonstrated nonspecific multiple scattered foci of hyperintense signal involving the subcortical supratentorial white matter without abnormal enhancement, most likely representing nonactive demyelinating plaques (FIGURES 1B and 1C).

Dx is revisited. Our patient was referred to an NMO clinic for evaluation. After further testing (including a repeat MRI based on the neurologist’s specifications, anti-aquaporin antibody testing, and MOG-antibody testing) and case discussion, it was determined that the patient had MOG-antibody disease. This disease, along with NMO, comprise a spectrum of disorders referred to as neuromyelitis optica spectrum disorder (NMOSD).

The patient was subsequently prescribed a rituximab infusion, 500 mg/50 mL, to treat the current attack. One infusion was to be completed weekly for 2 weeks with plans to repeat treatment every 6 months to prevent flares of NMO. During the first dose, the patient had a reaction to the treatment, which caused pruritus and chest tightness. She was able to complete the infusion after being treated with diphenhydramine.

Tx continued. In order to complete the second of 2 infusions of rituximab, the patient was pretreated with oral methylprednisolone the night before the infusion, along with diphenhydramine and acetaminophen on the day of treatment. Fortunately, the patient tolerated the infusion well with no adverse effects or reactions.

Continue to: DISCUSSION

DISCUSSION

Within the NMO spectrum, the MOG antibody is positive in up to 42% of AQP4-seronegative cases.⁶ MOG is a minor myelin component that is expressed exclusively in the central nervous system on the surface of myelin and oligodendrocyte processes. The role of this glycoprotein is not well understood but is hypothesized to function as a cell surface receptor or cell adhesion molecule.⁷

Among a cohort of 252 patients from the United Kingdom who tested positive for the MOG-IgG1 antibody, optic neuritis was seen in 55%, while 18% experienced transverse myelitis, and 15% had a history of area postrema syndrome. A brain MRI identified lesions in all areas of the brain including the brain stem, cerebellum, and cerebral hemispheres.⁸

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein Barr virus seropositivity, and tobacco abuse.

Differential diagnosis. Many diseases or conditions that are inflammatory, autoimmune, infectious, or neoplastic can involve the central nervous system and mimic the clinical and radiologic phenotypes of NMOSD-AQP4. They include lupus, SjÖgren’s syndrome, multiple sclerosis, sarcoidosis, acute disseminated encephalomyelitis, HIV, and vitamin B₁₂ deficiency.

Treatment. The standard treatment is intravenous methylprednisolone, 1 g/d for 3 to 5 days followed by a steroid taper. Therapeutic plasma exchange is recommended for refractory cases and in patients with spinal cord demyelination.^9-11 Rituximab is the first-line therapy for attack prevention^12-15 in NMOSD broadly and may be effective in MOG antibody disease, as well. In an open-label study of patients with NMOSD treated with rituximab, 64% were relapse free at follow-up, which ranged from 12 to 67 months.¹³ In a long-term study of patients treated with rituximab, 87% maintained a reduced relapse rate and 93% had improvement or stability over a 5-year follow-up.¹⁴

Continue to: Our patient

Our patient. After her diagnosis of NMOSD/MOG-antibody disease, our patient’s symptoms progressed to include vertigo, vestibular ataxia, pruritus, left foot drop, lower extremity numbness, and decreased hearing. After the second rituximab infusion her symptoms continued, but over time stabilized and have not worsened. She currently receives gabapentin 300 mg every 8 hours, as needed, for extremity numbness (which has been working well) along with sertraline 100 mg/d for depression.

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein-Barr virus seropositivity, and tobacco abuse.

Subsequent office visits have showed no further weight loss. Based on the current response to the rituximab, her prognosis is undetermined by Neurology as they continue to monitor for progression.

THE TAKEAWAY

Vestibular ataxia, foot drop, pruritus, vertigo, decreased hearing, numbness, and oculomotor dysfunction in the presence of nausea and vomiting should raise suspicion for NMOSD. The presence of AQP4 antibodies along with demyelinating central nervous system lesions, is highly indicative of NMO. The presence of MOG antibodies may indicate NMOSD/MOG-antibody disease. The initial treatment of NMOSD is intravenous methylprednisolone, which can be followed by treatment with rituximab to achieve remission.

CORRESPONDENCE
Daniel Murphy, MD, FAAFP, Department of Family and Community Medicine, Texas Tech University Health Science Center El Paso, 9849 Kenworthy Street, El Paso, Texas 79924; [email protected]

THE CASE

A 26-year-old Hispanic/African American woman presented to our clinic with a 2-month history of nausea and vomiting, along with dizziness. The nausea and vomiting persistently worsened, and she was only able to tolerate apples and berries. During this 2-month period, she lost 20 pounds and her symptoms progressed to include pruritus, ataxia, and mild hearing loss, with reoccurring episodes of falls.

THE DIAGNOSIS

On examination, she was found to be bradycardic with a heart rate of 47 beats/min, right- axis deviation, and inverted T waves in leads I, II, and augmented vector left. Her family history included the death of an aunt who was in her early 30s due to an unknown heart condition.

Echocardiogram identified mild mitral valve regurgitation with an ejection fraction of 55% to 60% (reference range: 55%-70%). Cardiology determined that her bradycardia was not the source of her symptoms. A neurologic exam identified 3+ hyperreflexia (indicating the reflex was increased), tandem gait instability, and left oculomotor dysfunction.

Brain magnetic resonance imaging (MRI) identified bilateral parietal white matter lesions where a demyelinating process could not be excluded (FIGURE 1A). The patient’s symptoms of nausea and vomiting continued, and she only tolerated peanuts and liquids. An MRI of the spine was negative.

Laboratory testing revealed that the patient was negative for human immunodeficiency virus (HIV), syphilis, Lyme disease, and lupus. Her thyroid-stimulating hormone level was 1.7 mIU/L (reference range: 0.4-4.2 mIU/L), and her vitamin B₁₂ level was 504 pg/mL (reference range: 160-950 pg/mL).

The patient’s lumbar puncture was negative for oligoclonal bands. The IgG synthesis rate/index cerebrospinal fluid (CSF) was –3.9, ruling out multiple sclerosis. Her CSF culture was negative, with a glucose level of 42 mg/dL (reference range: 70-110 mg/dL), colorless appearance, 1 white blood cell, and spinal albumin of 12.2 mg/dL (reference range: 8-42 mg/dL). The visual evoked potential was negative. The aquaporin-4 (AQP4) antibody was positive at 3.4 U/mL, and the myelin oligodendrocyte glycoprotein (MOG) antibody was positive.

Gastroenterology concluded a normal gastric accommodation and unremarkable computed tomography (CT) enterography. Moderate erosions were identified in the stomach with an erythematous gastropathy. The patient was placed on a proton pump inhibitor.

Continue to: Following the examination...

Following the examination and laboratory testing, the patient was admitted under our family medicine service for neuromyelitis optica (NMO) affecting the area postrema. NMO, also known as Devic’s disease, is an autoimmune disorder that affects the spinal cord and optic nerves. Autoantibodies against AQP4 are created in the periphery and are directed against astrocytes in the central nervous system. These antibodies bind to the foot processes of astrocytes, inducing complement-mediated cell damage and granulocyte infiltration.^1-5

Intravenous methylprednisolone was initiated at 250 mg every 6 hours for 3 days. A repeat brain MRI demonstrated nonspecific multiple scattered foci of hyperintense signal involving the subcortical supratentorial white matter without abnormal enhancement, most likely representing nonactive demyelinating plaques (FIGURES 1B and 1C).

Dx is revisited. Our patient was referred to an NMO clinic for evaluation. After further testing (including a repeat MRI based on the neurologist’s specifications, anti-aquaporin antibody testing, and MOG-antibody testing) and case discussion, it was determined that the patient had MOG-antibody disease. This disease, along with NMO, comprise a spectrum of disorders referred to as neuromyelitis optica spectrum disorder (NMOSD).

The patient was subsequently prescribed a rituximab infusion, 500 mg/50 mL, to treat the current attack. One infusion was to be completed weekly for 2 weeks with plans to repeat treatment every 6 months to prevent flares of NMO. During the first dose, the patient had a reaction to the treatment, which caused pruritus and chest tightness. She was able to complete the infusion after being treated with diphenhydramine.

Tx continued. In order to complete the second of 2 infusions of rituximab, the patient was pretreated with oral methylprednisolone the night before the infusion, along with diphenhydramine and acetaminophen on the day of treatment. Fortunately, the patient tolerated the infusion well with no adverse effects or reactions.

Continue to: DISCUSSION

DISCUSSION

Within the NMO spectrum, the MOG antibody is positive in up to 42% of AQP4-seronegative cases.⁶ MOG is a minor myelin component that is expressed exclusively in the central nervous system on the surface of myelin and oligodendrocyte processes. The role of this glycoprotein is not well understood but is hypothesized to function as a cell surface receptor or cell adhesion molecule.⁷

Among a cohort of 252 patients from the United Kingdom who tested positive for the MOG-IgG1 antibody, optic neuritis was seen in 55%, while 18% experienced transverse myelitis, and 15% had a history of area postrema syndrome. A brain MRI identified lesions in all areas of the brain including the brain stem, cerebellum, and cerebral hemispheres.⁸

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein Barr virus seropositivity, and tobacco abuse.

Differential diagnosis. Many diseases or conditions that are inflammatory, autoimmune, infectious, or neoplastic can involve the central nervous system and mimic the clinical and radiologic phenotypes of NMOSD-AQP4. They include lupus, SjÖgren’s syndrome, multiple sclerosis, sarcoidosis, acute disseminated encephalomyelitis, HIV, and vitamin B₁₂ deficiency.

Treatment. The standard treatment is intravenous methylprednisolone, 1 g/d for 3 to 5 days followed by a steroid taper. Therapeutic plasma exchange is recommended for refractory cases and in patients with spinal cord demyelination.^9-11 Rituximab is the first-line therapy for attack prevention^12-15 in NMOSD broadly and may be effective in MOG antibody disease, as well. In an open-label study of patients with NMOSD treated with rituximab, 64% were relapse free at follow-up, which ranged from 12 to 67 months.¹³ In a long-term study of patients treated with rituximab, 87% maintained a reduced relapse rate and 93% had improvement or stability over a 5-year follow-up.¹⁴

Continue to: Our patient

Our patient. After her diagnosis of NMOSD/MOG-antibody disease, our patient’s symptoms progressed to include vertigo, vestibular ataxia, pruritus, left foot drop, lower extremity numbness, and decreased hearing. After the second rituximab infusion her symptoms continued, but over time stabilized and have not worsened. She currently receives gabapentin 300 mg every 8 hours, as needed, for extremity numbness (which has been working well) along with sertraline 100 mg/d for depression.

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein-Barr virus seropositivity, and tobacco abuse.

Subsequent office visits have showed no further weight loss. Based on the current response to the rituximab, her prognosis is undetermined by Neurology as they continue to monitor for progression.

THE TAKEAWAY

Vestibular ataxia, foot drop, pruritus, vertigo, decreased hearing, numbness, and oculomotor dysfunction in the presence of nausea and vomiting should raise suspicion for NMOSD. The presence of AQP4 antibodies along with demyelinating central nervous system lesions, is highly indicative of NMO. The presence of MOG antibodies may indicate NMOSD/MOG-antibody disease. The initial treatment of NMOSD is intravenous methylprednisolone, which can be followed by treatment with rituximab to achieve remission.

CORRESPONDENCE
Daniel Murphy, MD, FAAFP, Department of Family and Community Medicine, Texas Tech University Health Science Center El Paso, 9849 Kenworthy Street, El Paso, Texas 79924; [email protected]

THE CASE

A 26-year-old Hispanic/African American woman presented to our clinic with a 2-month history of nausea and vomiting, along with dizziness. The nausea and vomiting persistently worsened, and she was only able to tolerate apples and berries. During this 2-month period, she lost 20 pounds and her symptoms progressed to include pruritus, ataxia, and mild hearing loss, with reoccurring episodes of falls.

THE DIAGNOSIS

On examination, she was found to be bradycardic with a heart rate of 47 beats/min, right- axis deviation, and inverted T waves in leads I, II, and augmented vector left. Her family history included the death of an aunt who was in her early 30s due to an unknown heart condition.

Echocardiogram identified mild mitral valve regurgitation with an ejection fraction of 55% to 60% (reference range: 55%-70%). Cardiology determined that her bradycardia was not the source of her symptoms. A neurologic exam identified 3+ hyperreflexia (indicating the reflex was increased), tandem gait instability, and left oculomotor dysfunction.

Brain magnetic resonance imaging (MRI) identified bilateral parietal white matter lesions where a demyelinating process could not be excluded (FIGURE 1A). The patient’s symptoms of nausea and vomiting continued, and she only tolerated peanuts and liquids. An MRI of the spine was negative.

Laboratory testing revealed that the patient was negative for human immunodeficiency virus (HIV), syphilis, Lyme disease, and lupus. Her thyroid-stimulating hormone level was 1.7 mIU/L (reference range: 0.4-4.2 mIU/L), and her vitamin B₁₂ level was 504 pg/mL (reference range: 160-950 pg/mL).

The patient’s lumbar puncture was negative for oligoclonal bands. The IgG synthesis rate/index cerebrospinal fluid (CSF) was –3.9, ruling out multiple sclerosis. Her CSF culture was negative, with a glucose level of 42 mg/dL (reference range: 70-110 mg/dL), colorless appearance, 1 white blood cell, and spinal albumin of 12.2 mg/dL (reference range: 8-42 mg/dL). The visual evoked potential was negative. The aquaporin-4 (AQP4) antibody was positive at 3.4 U/mL, and the myelin oligodendrocyte glycoprotein (MOG) antibody was positive.

Gastroenterology concluded a normal gastric accommodation and unremarkable computed tomography (CT) enterography. Moderate erosions were identified in the stomach with an erythematous gastropathy. The patient was placed on a proton pump inhibitor.

Continue to: Following the examination...

Following the examination and laboratory testing, the patient was admitted under our family medicine service for neuromyelitis optica (NMO) affecting the area postrema. NMO, also known as Devic’s disease, is an autoimmune disorder that affects the spinal cord and optic nerves. Autoantibodies against AQP4 are created in the periphery and are directed against astrocytes in the central nervous system. These antibodies bind to the foot processes of astrocytes, inducing complement-mediated cell damage and granulocyte infiltration.^1-5

Intravenous methylprednisolone was initiated at 250 mg every 6 hours for 3 days. A repeat brain MRI demonstrated nonspecific multiple scattered foci of hyperintense signal involving the subcortical supratentorial white matter without abnormal enhancement, most likely representing nonactive demyelinating plaques (FIGURES 1B and 1C).

Dx is revisited. Our patient was referred to an NMO clinic for evaluation. After further testing (including a repeat MRI based on the neurologist’s specifications, anti-aquaporin antibody testing, and MOG-antibody testing) and case discussion, it was determined that the patient had MOG-antibody disease. This disease, along with NMO, comprise a spectrum of disorders referred to as neuromyelitis optica spectrum disorder (NMOSD).

The patient was subsequently prescribed a rituximab infusion, 500 mg/50 mL, to treat the current attack. One infusion was to be completed weekly for 2 weeks with plans to repeat treatment every 6 months to prevent flares of NMO. During the first dose, the patient had a reaction to the treatment, which caused pruritus and chest tightness. She was able to complete the infusion after being treated with diphenhydramine.

Tx continued. In order to complete the second of 2 infusions of rituximab, the patient was pretreated with oral methylprednisolone the night before the infusion, along with diphenhydramine and acetaminophen on the day of treatment. Fortunately, the patient tolerated the infusion well with no adverse effects or reactions.

Continue to: DISCUSSION

DISCUSSION

Within the NMO spectrum, the MOG antibody is positive in up to 42% of AQP4-seronegative cases.⁶ MOG is a minor myelin component that is expressed exclusively in the central nervous system on the surface of myelin and oligodendrocyte processes. The role of this glycoprotein is not well understood but is hypothesized to function as a cell surface receptor or cell adhesion molecule.⁷

Among a cohort of 252 patients from the United Kingdom who tested positive for the MOG-IgG1 antibody, optic neuritis was seen in 55%, while 18% experienced transverse myelitis, and 15% had a history of area postrema syndrome. A brain MRI identified lesions in all areas of the brain including the brain stem, cerebellum, and cerebral hemispheres.⁸

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein Barr virus seropositivity, and tobacco abuse.

Differential diagnosis. Many diseases or conditions that are inflammatory, autoimmune, infectious, or neoplastic can involve the central nervous system and mimic the clinical and radiologic phenotypes of NMOSD-AQP4. They include lupus, SjÖgren’s syndrome, multiple sclerosis, sarcoidosis, acute disseminated encephalomyelitis, HIV, and vitamin B₁₂ deficiency.

Treatment. The standard treatment is intravenous methylprednisolone, 1 g/d for 3 to 5 days followed by a steroid taper. Therapeutic plasma exchange is recommended for refractory cases and in patients with spinal cord demyelination.^9-11 Rituximab is the first-line therapy for attack prevention^12-15 in NMOSD broadly and may be effective in MOG antibody disease, as well. In an open-label study of patients with NMOSD treated with rituximab, 64% were relapse free at follow-up, which ranged from 12 to 67 months.¹³ In a long-term study of patients treated with rituximab, 87% maintained a reduced relapse rate and 93% had improvement or stability over a 5-year follow-up.¹⁴

Continue to: Our patient

Our patient. After her diagnosis of NMOSD/MOG-antibody disease, our patient’s symptoms progressed to include vertigo, vestibular ataxia, pruritus, left foot drop, lower extremity numbness, and decreased hearing. After the second rituximab infusion her symptoms continued, but over time stabilized and have not worsened. She currently receives gabapentin 300 mg every 8 hours, as needed, for extremity numbness (which has been working well) along with sertraline 100 mg/d for depression.

Risk factors for NMOSD include female gender, Asian and African ethnicities, Epstein-Barr virus seropositivity, and tobacco abuse.

Subsequent office visits have showed no further weight loss. Based on the current response to the rituximab, her prognosis is undetermined by Neurology as they continue to monitor for progression.

THE TAKEAWAY

Vestibular ataxia, foot drop, pruritus, vertigo, decreased hearing, numbness, and oculomotor dysfunction in the presence of nausea and vomiting should raise suspicion for NMOSD. The presence of AQP4 antibodies along with demyelinating central nervous system lesions, is highly indicative of NMO. The presence of MOG antibodies may indicate NMOSD/MOG-antibody disease. The initial treatment of NMOSD is intravenous methylprednisolone, which can be followed by treatment with rituximab to achieve remission.

CORRESPONDENCE
Daniel Murphy, MD, FAAFP, Department of Family and Community Medicine, Texas Tech University Health Science Center El Paso, 9849 Kenworthy Street, El Paso, Texas 79924; [email protected]

ILLUSTRATIVE CASE

A 54-year-old woman with a history of hypertension presents with a chief complaint of dizziness. You require an assessment of orthostatic vital signs to proceed. In your busy clinical practice, when should assessment take place to be most useful?

Orthostatic hypotension (OH) is defined as a postural reduction in systolic blood pressure (BP) of ≥ 20 mm Hg or diastolic BP of ≥ 10 mm Hg, measured within 3 minutes of rising from supine to standing. This definition is based on consensus guidelines from the American Academy of Neurology and the American Autonomic Society² and has been upheld by European guidelines.³

The prevalence of OH is approximately 6% in the general population, with estimates ranging from 10% to 55% in older adults.^{4 ­}Etiology is often multifactorial; causes may be neurogenic (mediated by autonomic failure as in Parkinson’s disease, multiple system atrophy, or diabetic neuropathy), non-­neurogenic (related to medications or hypovolemia), or idiopathic.

It’s important to identify OH because of its associated increase in morbidities, such as an increased risk of falls (hazard ratio [HR] = 1.5),⁵ coronary heart disease (HR = 1.3), stroke (HR = 1.2), and all-cause mortality (HR = 1.4).⁶ Treatments include physical maneuvers (getting up slowly, leg crossing, and muscle clenching), increased salt and water intake, compression stockings, the addition of medications (such as fludrocortisone or midodrine), and the avoidance of other medications (such as benzodiazepines and diuretics).

The guideline-recommended 3-minute delay in assessment can be impractical in a busy clinical setting. Using data from the Atherosclerosis Risk in Communities (ARIC) study, investigators correlated the timing of measurements of postural change in BP with long-term adverse outcomes.¹

STUDY SUMMARY

Early vs late OH assessment in middle-aged adults

The ARIC study is a longitudinal, prospective, cohort study of almost 16,000 adults followed since 1987. Juraschek et al¹ assessed the optimal time to identify OH and its association with the adverse clinical outcomes of fall, fracture, syncope, motor vehicle crash, and mortality. The researchers sought to discover whether BP measurements determined immediately after standing predict adverse events as well as BP measurements taken closer to 3 minutes.

Study participants were between the ages of 45 and 64 years (mean 54 years), and 26% were black and 54% were female. They lived in 4 different US communities. The researchers excluded patients with missing OH assessments or other relevant cohort or historical data, leaving a cohort of 11,429 subjects.

Continue to: As part of their...

As part of their enrollment into the ARIC study, subjects had their BP measurements taken 2 to 5 times in the lying position (90% of participants had ≥ 4 measurements) and after standing (91% participants had ≥ 4 measurements) using a programmable automatic BP cuff. All 5 standing BP measurements (taken at a mean of 28, 53, 76, 100, and 116 seconds after standing) were measured for 7385 out of 11,429 (64.6%) participants. Subjects were asked if he or she “usually gets dizzy on standing up.”

This study found that orthostatic hypotension identified within 1 minute of standing was more clinically meaningful than OH identified after 1 minute.

Researchers determined the association between OH and postural change in systolic BP or postural change in diastolic BP with history of dizziness after standing. They also determined the incidence of falls, fracture, syncope, motor vehicle crash, and mortality via a review of hospitalizations and billing for Medicaid and Medicare services. Subjects were followed for a median of 23 years.

Results

Of the entire cohort, 1138 (10%) reported dizziness on standing. Only OH identified at the first BP measurement (mean 28 secs) was associated with a history of dizziness upon standing (odds ratio [OR] = 1.49; 95% confidence interval [CI], 1.18-1.89). Also, it was associated with the highest incidence of fracture, syncope, and death (18.9, 17, and 31.4 per 1000 person-years, respectively).

After adjusting for age, sex, and multiple other cardiovascular risk factors, the risk of falls was significantly associated with OH at BP measurements 1 to 4, but was most strongly associated with BP measurement 2 (taken at a mean of 53 secs after standing) (HR = 1.29; 95% CI, 1.12-1.49), which translates to 13.2 falls per 1000 patient-years. Fracture was associated with OH at measurements 1 (HR = 1.16; 95% CI, 1.01-1.34) and 2 (HR = 1.14; 95% CI, 1.01-1.29). Motor vehicle crashes were associated only with BP measurement 2 (HR = 1.43; 95% CI, 1.04-1.96). Finally, risk of syncope and risk of death were statistically associated with the presence of OH at all 5 BP measurements.

WHAT’S NEW

Earlier OH assessments are more informative than late ones

This study found OH identified within 1 minute of standing to be more clinically meaningful than OH identified after 1 minute. Also, the findings reinforce the relationship between OH and adverse events, including injury and overall mortality. Evaluation for OH performed only at 3 minutes may miss symptomatic OH.

Continue to: CAVEATS

Could a healthy population skew the results?

The population in this study was relatively healthy, with a lower prevalence of diabetes and coronary artery disease than the general population. While there is no reason to expect detection of OH to differ in a population with more comorbidities, the possibility exists.

If OH is not identified in < 1 minute of standing, standard OH evaluation within 3 minutes after standing should be performed, as OH identified at any time point after standing is associated with adverse events and increased mortality.

This study did not address the effects of medical intervention for OH on injury or mortality. Also, whether OH is the direct cause of the adverse outcomes or a marker for other disease is unknown.

CHALLENGES TO IMPLEMENTATION

A change to protocols and guidelines

Although none were noted, any change in practice requires updating clinical protocols and guidelines, which can take time.

ACKNOWLEDGMENT

The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.

ILLUSTRATIVE CASE

A 54-year-old woman with a history of hypertension presents with a chief complaint of dizziness. You require an assessment of orthostatic vital signs to proceed. In your busy clinical practice, when should assessment take place to be most useful?

Orthostatic hypotension (OH) is defined as a postural reduction in systolic blood pressure (BP) of ≥ 20 mm Hg or diastolic BP of ≥ 10 mm Hg, measured within 3 minutes of rising from supine to standing. This definition is based on consensus guidelines from the American Academy of Neurology and the American Autonomic Society² and has been upheld by European guidelines.³

The prevalence of OH is approximately 6% in the general population, with estimates ranging from 10% to 55% in older adults.^{4 ­}Etiology is often multifactorial; causes may be neurogenic (mediated by autonomic failure as in Parkinson’s disease, multiple system atrophy, or diabetic neuropathy), non-­neurogenic (related to medications or hypovolemia), or idiopathic.

It’s important to identify OH because of its associated increase in morbidities, such as an increased risk of falls (hazard ratio [HR] = 1.5),⁵ coronary heart disease (HR = 1.3), stroke (HR = 1.2), and all-cause mortality (HR = 1.4).⁶ Treatments include physical maneuvers (getting up slowly, leg crossing, and muscle clenching), increased salt and water intake, compression stockings, the addition of medications (such as fludrocortisone or midodrine), and the avoidance of other medications (such as benzodiazepines and diuretics).

The guideline-recommended 3-minute delay in assessment can be impractical in a busy clinical setting. Using data from the Atherosclerosis Risk in Communities (ARIC) study, investigators correlated the timing of measurements of postural change in BP with long-term adverse outcomes.¹

STUDY SUMMARY

Early vs late OH assessment in middle-aged adults

The ARIC study is a longitudinal, prospective, cohort study of almost 16,000 adults followed since 1987. Juraschek et al¹ assessed the optimal time to identify OH and its association with the adverse clinical outcomes of fall, fracture, syncope, motor vehicle crash, and mortality. The researchers sought to discover whether BP measurements determined immediately after standing predict adverse events as well as BP measurements taken closer to 3 minutes.

Study participants were between the ages of 45 and 64 years (mean 54 years), and 26% were black and 54% were female. They lived in 4 different US communities. The researchers excluded patients with missing OH assessments or other relevant cohort or historical data, leaving a cohort of 11,429 subjects.

Continue to: As part of their...

As part of their enrollment into the ARIC study, subjects had their BP measurements taken 2 to 5 times in the lying position (90% of participants had ≥ 4 measurements) and after standing (91% participants had ≥ 4 measurements) using a programmable automatic BP cuff. All 5 standing BP measurements (taken at a mean of 28, 53, 76, 100, and 116 seconds after standing) were measured for 7385 out of 11,429 (64.6%) participants. Subjects were asked if he or she “usually gets dizzy on standing up.”

This study found that orthostatic hypotension identified within 1 minute of standing was more clinically meaningful than OH identified after 1 minute.

Researchers determined the association between OH and postural change in systolic BP or postural change in diastolic BP with history of dizziness after standing. They also determined the incidence of falls, fracture, syncope, motor vehicle crash, and mortality via a review of hospitalizations and billing for Medicaid and Medicare services. Subjects were followed for a median of 23 years.

Results

Of the entire cohort, 1138 (10%) reported dizziness on standing. Only OH identified at the first BP measurement (mean 28 secs) was associated with a history of dizziness upon standing (odds ratio [OR] = 1.49; 95% confidence interval [CI], 1.18-1.89). Also, it was associated with the highest incidence of fracture, syncope, and death (18.9, 17, and 31.4 per 1000 person-years, respectively).

After adjusting for age, sex, and multiple other cardiovascular risk factors, the risk of falls was significantly associated with OH at BP measurements 1 to 4, but was most strongly associated with BP measurement 2 (taken at a mean of 53 secs after standing) (HR = 1.29; 95% CI, 1.12-1.49), which translates to 13.2 falls per 1000 patient-years. Fracture was associated with OH at measurements 1 (HR = 1.16; 95% CI, 1.01-1.34) and 2 (HR = 1.14; 95% CI, 1.01-1.29). Motor vehicle crashes were associated only with BP measurement 2 (HR = 1.43; 95% CI, 1.04-1.96). Finally, risk of syncope and risk of death were statistically associated with the presence of OH at all 5 BP measurements.

WHAT’S NEW

Earlier OH assessments are more informative than late ones

This study found OH identified within 1 minute of standing to be more clinically meaningful than OH identified after 1 minute. Also, the findings reinforce the relationship between OH and adverse events, including injury and overall mortality. Evaluation for OH performed only at 3 minutes may miss symptomatic OH.

Continue to: CAVEATS

Could a healthy population skew the results?

The population in this study was relatively healthy, with a lower prevalence of diabetes and coronary artery disease than the general population. While there is no reason to expect detection of OH to differ in a population with more comorbidities, the possibility exists.

If OH is not identified in < 1 minute of standing, standard OH evaluation within 3 minutes after standing should be performed, as OH identified at any time point after standing is associated with adverse events and increased mortality.

This study did not address the effects of medical intervention for OH on injury or mortality. Also, whether OH is the direct cause of the adverse outcomes or a marker for other disease is unknown.

CHALLENGES TO IMPLEMENTATION

A change to protocols and guidelines

Although none were noted, any change in practice requires updating clinical protocols and guidelines, which can take time.

ACKNOWLEDGMENT

The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.

ILLUSTRATIVE CASE

A 54-year-old woman with a history of hypertension presents with a chief complaint of dizziness. You require an assessment of orthostatic vital signs to proceed. In your busy clinical practice, when should assessment take place to be most useful?

Orthostatic hypotension (OH) is defined as a postural reduction in systolic blood pressure (BP) of ≥ 20 mm Hg or diastolic BP of ≥ 10 mm Hg, measured within 3 minutes of rising from supine to standing. This definition is based on consensus guidelines from the American Academy of Neurology and the American Autonomic Society² and has been upheld by European guidelines.³

The prevalence of OH is approximately 6% in the general population, with estimates ranging from 10% to 55% in older adults.^{4 ­}Etiology is often multifactorial; causes may be neurogenic (mediated by autonomic failure as in Parkinson’s disease, multiple system atrophy, or diabetic neuropathy), non-­neurogenic (related to medications or hypovolemia), or idiopathic.

It’s important to identify OH because of its associated increase in morbidities, such as an increased risk of falls (hazard ratio [HR] = 1.5),⁵ coronary heart disease (HR = 1.3), stroke (HR = 1.2), and all-cause mortality (HR = 1.4).⁶ Treatments include physical maneuvers (getting up slowly, leg crossing, and muscle clenching), increased salt and water intake, compression stockings, the addition of medications (such as fludrocortisone or midodrine), and the avoidance of other medications (such as benzodiazepines and diuretics).

The guideline-recommended 3-minute delay in assessment can be impractical in a busy clinical setting. Using data from the Atherosclerosis Risk in Communities (ARIC) study, investigators correlated the timing of measurements of postural change in BP with long-term adverse outcomes.¹

STUDY SUMMARY

Early vs late OH assessment in middle-aged adults

The ARIC study is a longitudinal, prospective, cohort study of almost 16,000 adults followed since 1987. Juraschek et al¹ assessed the optimal time to identify OH and its association with the adverse clinical outcomes of fall, fracture, syncope, motor vehicle crash, and mortality. The researchers sought to discover whether BP measurements determined immediately after standing predict adverse events as well as BP measurements taken closer to 3 minutes.

Study participants were between the ages of 45 and 64 years (mean 54 years), and 26% were black and 54% were female. They lived in 4 different US communities. The researchers excluded patients with missing OH assessments or other relevant cohort or historical data, leaving a cohort of 11,429 subjects.

Continue to: As part of their...

As part of their enrollment into the ARIC study, subjects had their BP measurements taken 2 to 5 times in the lying position (90% of participants had ≥ 4 measurements) and after standing (91% participants had ≥ 4 measurements) using a programmable automatic BP cuff. All 5 standing BP measurements (taken at a mean of 28, 53, 76, 100, and 116 seconds after standing) were measured for 7385 out of 11,429 (64.6%) participants. Subjects were asked if he or she “usually gets dizzy on standing up.”

This study found that orthostatic hypotension identified within 1 minute of standing was more clinically meaningful than OH identified after 1 minute.

Researchers determined the association between OH and postural change in systolic BP or postural change in diastolic BP with history of dizziness after standing. They also determined the incidence of falls, fracture, syncope, motor vehicle crash, and mortality via a review of hospitalizations and billing for Medicaid and Medicare services. Subjects were followed for a median of 23 years.

Results

Of the entire cohort, 1138 (10%) reported dizziness on standing. Only OH identified at the first BP measurement (mean 28 secs) was associated with a history of dizziness upon standing (odds ratio [OR] = 1.49; 95% confidence interval [CI], 1.18-1.89). Also, it was associated with the highest incidence of fracture, syncope, and death (18.9, 17, and 31.4 per 1000 person-years, respectively).

After adjusting for age, sex, and multiple other cardiovascular risk factors, the risk of falls was significantly associated with OH at BP measurements 1 to 4, but was most strongly associated with BP measurement 2 (taken at a mean of 53 secs after standing) (HR = 1.29; 95% CI, 1.12-1.49), which translates to 13.2 falls per 1000 patient-years. Fracture was associated with OH at measurements 1 (HR = 1.16; 95% CI, 1.01-1.34) and 2 (HR = 1.14; 95% CI, 1.01-1.29). Motor vehicle crashes were associated only with BP measurement 2 (HR = 1.43; 95% CI, 1.04-1.96). Finally, risk of syncope and risk of death were statistically associated with the presence of OH at all 5 BP measurements.

WHAT’S NEW

Earlier OH assessments are more informative than late ones

This study found OH identified within 1 minute of standing to be more clinically meaningful than OH identified after 1 minute. Also, the findings reinforce the relationship between OH and adverse events, including injury and overall mortality. Evaluation for OH performed only at 3 minutes may miss symptomatic OH.

Continue to: CAVEATS

Could a healthy population skew the results?

The population in this study was relatively healthy, with a lower prevalence of diabetes and coronary artery disease than the general population. While there is no reason to expect detection of OH to differ in a population with more comorbidities, the possibility exists.

If OH is not identified in < 1 minute of standing, standard OH evaluation within 3 minutes after standing should be performed, as OH identified at any time point after standing is associated with adverse events and increased mortality.

This study did not address the effects of medical intervention for OH on injury or mortality. Also, whether OH is the direct cause of the adverse outcomes or a marker for other disease is unknown.

CHALLENGES TO IMPLEMENTATION

A change to protocols and guidelines

Although none were noted, any change in practice requires updating clinical protocols and guidelines, which can take time.

ACKNOWLEDGMENT

The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.

THE CASE

Emily T,* a 30-year-old woman, visited her primary care physician as follow-up to reassess her grief over the loss of her father a year earlier. Emily was her father’s primary caretaker and still lived alone in his home. Emily had a history of chronic pain and major depressive disorder and had expressed feelings of worthlessness and hopelessness about her future since her father’s passing. In addition to her continuing grief response, she reported feeling worse on most days. She completed the Patient Health Questionnaire-9, and results indicated anhedonia, depressed mood, psychomotor retardation, hypersomnia, decreased appetite, decreased concentration, and thoughts that she would be better off dead.

• HOW WOULD YOU PROCEED WITH THIS PATIENT?

* The patient’s name has been changed to protect her identity.

In the United States, 1 suicide occurs on average every 12 minutes; lifetime prevalence of suicide attempts ranges from 1.9% to 8.7%.¹ Suicide is the 10th overall cause of death in the United States, and it is the second leading cause of death for adults 18 to 34 years of age.² In one study, nearly half of suicide victims had contact with primary care providers within 1 month of their suicide.³ Unfortunately, additional research suggests that primary care physicians appropriately screen for suicide in fewer than 40% of patient encounters.^4,5

Suicide is defined as “death caused by self-directed injurious behavior with any intent to die as a result of the behavior.”⁶ When screening for suicide, be aware of the many terms related to suicide evaluation (TABLE 1⁶). Be mindful, too, of the differences between suicidal and nonsuicidal ideation (death wish); the continuum of such thoughts ranges from those that lead to suicide to those that do not.

SUICIDE SCREENING RECOMMENDATIONS VARY

Although most health care providers would agree that intervening with a suicidal patient first requires competence in assessing suicide risk, regulating bodies differ on the use of routine screening and on appropriate screening tools for primary care. The Joint Commission recommends assessing suicide risk with all primary care patients,⁷ while the US Preventive Services Tasks Force (USPSTF) advises against universal suicide screening in primary care⁸ due to insufficient evidence that its benefit outweighs potential harm (TABLE 2^7-12). Instead, the USPSTF recommends screening primary care patients with known mental health disorders, recent inpatient psychiatric hospitalization, prior suicide or self-harm attempts, or increased emotional distress.⁸ USPSTF does support screening for depression with routine mental health measures that include items assessing suicidality.^8,13,14 The American Academy of Family Physicians supports the recommendations by USPSTF.¹³

When screening for suicide, a comprehensive suicide risk assessment is recommended by both the Joint Commission and USPSTF.^7,8 A comprehensive suicide risk assessment has 4 components: (1) identification of current suicide risk factors, (2) identification of protective factors, (3) inquiry about suicidal ideation, intent, and plan, and (4) primary care practitioner judgment of risk level and plan for clinical intervention.^9-11

Take into account both risks and protective factors

Unfortunately, there is no “typical” description of a patient at risk for suicide and no validated models to predict suicide risk.^8,10 A multitude of factors, both individual and societal, can increase or reduce risk of suicide.^11,15 Each patient’s unique history includes risk factors for suicide including precipitating events (eg, job loss, termination of a relationship, death of a loved one) and protective factors that may be evaluated to determine overall risk for suicide (TABLE 3^8,10,11,15). According to the Centers for Disease Control and Prevention (CDC), there are several warning signs for patients who may be at greater risk for suicide: isolation, increased anxiety or anger, obtaining lethal means (eg, guns, knives, ropes), frequent mood swings, sleep changes, feeling trapped or in pain, increased substance use, discussing plans for death or wishes of death, and feeling like a burden.¹⁶

CHOOSING FROM AMONG SUICIDE SCREENING TOOLS

Brief mental health screening tools such as the Patient Health Questionnaire-9 (PHQ-9) are commonly used as primary screening tools for suicidal ideation.¹⁷ However, to attain a fuller understanding of a patient’s suicidality, select a screening tool that specifically focuses on suicidal ideation, intent, or plan, and then interview the patient (TABLE 4^10,11,15).

Continue to: Several screening tools...

Several screening tools are available for exploring a patient’s suicidality. Unfortunately, most of them are supported by limited evidence of effectiveness in identifying suicide risk.^8-10 An exception is the well-researched and commonly used Columbia-Suicide Severity Rating Scale (C-SSRS).^18,19 In a comparative study conducted at 2 primary care clinics, researchers found that the suicide item included in the PHQ-9 provided poor sensitivity but moderate specificity (60% and 84%, respectively),²⁰ while the C-SSRS showed high sensitivity (100%) and specificity (96%-100%) in accurately identifying various suicidal self-injurious behaviors above and beyond what was identified through a structured clinical interview.²⁰ Free copies of the C-SSRS, training materials, and follow-up assessments in multiple languages can be obtained on The Columbia Lighthouse Project Web site (http://cssrs.columbia.edu/).¹⁹

RECOMMENDATIONS FOR INTERVENTION

While there is debate regarding whom to screen for suicide, the importance of intervention when a patient is revealed to be at risk is clear. After completing a comprehensive suicide risk assessment, designate the patient’s level of risk as high, moderate, or low, and follow a stepped approach to clinical care (see the Assessment and Interventions with Potentially Suicidal Patients table (page 31) at https://www.sprc.org/sites/default/files/Final%20National%20Suicide%20Prevention%20Toolkit%202.15.18%20FINAL.pdf).¹¹ Provide any patient at risk, regardless of level, with contact information for local crisis and peer support as well as national resources (National Suicide Prevention Lifeline, (800) 273-TALK (8255), https://suicidepreventionlifeline.org/; Crisis Text Line, Text HOME to 741741, https://www.crisistextline.org/).

The Columbia- Suicide Severity Rating Scale has higher sensitivity and specificity for suicide risk than the PHQ-9.

When a patient is at high risk for suicide and reports an imminent plan or intent, ensure their safety through inpatient psychiatric hospitalization and then close follow-up upon hospital discharge. First encourage voluntary hospitalization in a collaborative discussion with the patient; resort to involuntary hospitalization only if the patient resists.

What not to do. When the patient does not require immediate hospitalization, evidence recommends against contracting for patient safety via a written contract or requiring patients to verbally guarantee that they will not commit suicide upon leaving a provider’s office.²¹ Concerns about such contracts include a lack of evidence supporting their use, decreased vigilance by health care workers when such contracts are in place, and questions regarding informed consent and competence.²¹ Instead, engage a patient who is at moderate or low risk in safety planning, and meet with the patient frequently to discuss continued safety planning through close follow-up (or with a behavioral health provider if available).^10-12,22 With patients previously identified as at high risk for suicide who return from inpatient psychiatric hospitalization, continue to screen them for suicide at subsequent visits and engage them in collaborative safety planning.

Safety planning (TABLE 5¹²), also known as crisis response planning, is considered a best practice and effective suicide prevention intervention by the Suicide Prevention Resource Center and the American Foundation for Suicide Prevention Best Practices Registry for Suicide Prevention.²³ Safety planning involves a collaboration between patient and physician to identify risk factors and protective factors along with crisis resources and strategies to reduce engagement in suicide behaviors.^12,22

Continue to: THE CASE

THE CASE

Based on the concerning results from the ­PHQ-9 suicide item, Emily’s physician conducted a comprehensive suicide risk assessment using both clinical interview and the C-SSRS. Emily reported that she was experiencing daily suicidal ideations due to a lack of social support and longing to be with her deceased father. She had not previously attempted suicide and had no imminent intent to commit suicide. Emily did, however, have a plan to overdose on opioid medications she had been collecting for many months. Her physician determined that Emily was at moderate risk for suicide and consulted with the clinic’s behavioral health consultant, a psychologist, to confirm a treatment plan.

After a comprehensive suicide risk assessment, determine the patient’s level of risk and follow a stepped approach to clinical care.

Emily and her physician collaboratively developed a safety plan including means reduction. Emily agreed to have her physician contact a friend to assist with safety planning, and she brought her opioid medications to the primary care clinic for disposal. Follow-up appointments were scheduled with the physician for every other week. The psychologist was available at the time of the first biweekly appointment to consult with the physician if needed. This initial appointment was focused on Emily’s suicide risk and her ability to engage in safety planning. In addition, the physician recommended that Emily schedule time with the psychologist so that she could work on her grief and depressive symptoms.

After several weeks of the biweekly appointments with both the primary care provider and the psychologist, Emily was no longer reporting suicidal ideation and she was ready to engage in coping strategies to deal with her grief and depressive symptoms.

CORRESPONDENCE
Meredith L.C. Williamson, PhD, 2900 E. 29th Street, Suite 100, Bryan, TX 77802; [email protected].

THE CASE

Emily T,* a 30-year-old woman, visited her primary care physician as follow-up to reassess her grief over the loss of her father a year earlier. Emily was her father’s primary caretaker and still lived alone in his home. Emily had a history of chronic pain and major depressive disorder and had expressed feelings of worthlessness and hopelessness about her future since her father’s passing. In addition to her continuing grief response, she reported feeling worse on most days. She completed the Patient Health Questionnaire-9, and results indicated anhedonia, depressed mood, psychomotor retardation, hypersomnia, decreased appetite, decreased concentration, and thoughts that she would be better off dead.

• HOW WOULD YOU PROCEED WITH THIS PATIENT?

* The patient’s name has been changed to protect her identity.

In the United States, 1 suicide occurs on average every 12 minutes; lifetime prevalence of suicide attempts ranges from 1.9% to 8.7%.¹ Suicide is the 10th overall cause of death in the United States, and it is the second leading cause of death for adults 18 to 34 years of age.² In one study, nearly half of suicide victims had contact with primary care providers within 1 month of their suicide.³ Unfortunately, additional research suggests that primary care physicians appropriately screen for suicide in fewer than 40% of patient encounters.^4,5

Suicide is defined as “death caused by self-directed injurious behavior with any intent to die as a result of the behavior.”⁶ When screening for suicide, be aware of the many terms related to suicide evaluation (TABLE 1⁶). Be mindful, too, of the differences between suicidal and nonsuicidal ideation (death wish); the continuum of such thoughts ranges from those that lead to suicide to those that do not.

SUICIDE SCREENING RECOMMENDATIONS VARY

Although most health care providers would agree that intervening with a suicidal patient first requires competence in assessing suicide risk, regulating bodies differ on the use of routine screening and on appropriate screening tools for primary care. The Joint Commission recommends assessing suicide risk with all primary care patients,⁷ while the US Preventive Services Tasks Force (USPSTF) advises against universal suicide screening in primary care⁸ due to insufficient evidence that its benefit outweighs potential harm (TABLE 2^7-12). Instead, the USPSTF recommends screening primary care patients with known mental health disorders, recent inpatient psychiatric hospitalization, prior suicide or self-harm attempts, or increased emotional distress.⁸ USPSTF does support screening for depression with routine mental health measures that include items assessing suicidality.^8,13,14 The American Academy of Family Physicians supports the recommendations by USPSTF.¹³

When screening for suicide, a comprehensive suicide risk assessment is recommended by both the Joint Commission and USPSTF.^7,8 A comprehensive suicide risk assessment has 4 components: (1) identification of current suicide risk factors, (2) identification of protective factors, (3) inquiry about suicidal ideation, intent, and plan, and (4) primary care practitioner judgment of risk level and plan for clinical intervention.^9-11

Take into account both risks and protective factors

Unfortunately, there is no “typical” description of a patient at risk for suicide and no validated models to predict suicide risk.^8,10 A multitude of factors, both individual and societal, can increase or reduce risk of suicide.^11,15 Each patient’s unique history includes risk factors for suicide including precipitating events (eg, job loss, termination of a relationship, death of a loved one) and protective factors that may be evaluated to determine overall risk for suicide (TABLE 3^8,10,11,15). According to the Centers for Disease Control and Prevention (CDC), there are several warning signs for patients who may be at greater risk for suicide: isolation, increased anxiety or anger, obtaining lethal means (eg, guns, knives, ropes), frequent mood swings, sleep changes, feeling trapped or in pain, increased substance use, discussing plans for death or wishes of death, and feeling like a burden.¹⁶

CHOOSING FROM AMONG SUICIDE SCREENING TOOLS

Brief mental health screening tools such as the Patient Health Questionnaire-9 (PHQ-9) are commonly used as primary screening tools for suicidal ideation.¹⁷ However, to attain a fuller understanding of a patient’s suicidality, select a screening tool that specifically focuses on suicidal ideation, intent, or plan, and then interview the patient (TABLE 4^10,11,15).

Continue to: Several screening tools...

Several screening tools are available for exploring a patient’s suicidality. Unfortunately, most of them are supported by limited evidence of effectiveness in identifying suicide risk.^8-10 An exception is the well-researched and commonly used Columbia-Suicide Severity Rating Scale (C-SSRS).^18,19 In a comparative study conducted at 2 primary care clinics, researchers found that the suicide item included in the PHQ-9 provided poor sensitivity but moderate specificity (60% and 84%, respectively),²⁰ while the C-SSRS showed high sensitivity (100%) and specificity (96%-100%) in accurately identifying various suicidal self-injurious behaviors above and beyond what was identified through a structured clinical interview.²⁰ Free copies of the C-SSRS, training materials, and follow-up assessments in multiple languages can be obtained on The Columbia Lighthouse Project Web site (http://cssrs.columbia.edu/).¹⁹

RECOMMENDATIONS FOR INTERVENTION

While there is debate regarding whom to screen for suicide, the importance of intervention when a patient is revealed to be at risk is clear. After completing a comprehensive suicide risk assessment, designate the patient’s level of risk as high, moderate, or low, and follow a stepped approach to clinical care (see the Assessment and Interventions with Potentially Suicidal Patients table (page 31) at https://www.sprc.org/sites/default/files/Final%20National%20Suicide%20Prevention%20Toolkit%202.15.18%20FINAL.pdf).¹¹ Provide any patient at risk, regardless of level, with contact information for local crisis and peer support as well as national resources (National Suicide Prevention Lifeline, (800) 273-TALK (8255), https://suicidepreventionlifeline.org/; Crisis Text Line, Text HOME to 741741, https://www.crisistextline.org/).

The Columbia- Suicide Severity Rating Scale has higher sensitivity and specificity for suicide risk than the PHQ-9.

When a patient is at high risk for suicide and reports an imminent plan or intent, ensure their safety through inpatient psychiatric hospitalization and then close follow-up upon hospital discharge. First encourage voluntary hospitalization in a collaborative discussion with the patient; resort to involuntary hospitalization only if the patient resists.

What not to do. When the patient does not require immediate hospitalization, evidence recommends against contracting for patient safety via a written contract or requiring patients to verbally guarantee that they will not commit suicide upon leaving a provider’s office.²¹ Concerns about such contracts include a lack of evidence supporting their use, decreased vigilance by health care workers when such contracts are in place, and questions regarding informed consent and competence.²¹ Instead, engage a patient who is at moderate or low risk in safety planning, and meet with the patient frequently to discuss continued safety planning through close follow-up (or with a behavioral health provider if available).^10-12,22 With patients previously identified as at high risk for suicide who return from inpatient psychiatric hospitalization, continue to screen them for suicide at subsequent visits and engage them in collaborative safety planning.

Safety planning (TABLE 5¹²), also known as crisis response planning, is considered a best practice and effective suicide prevention intervention by the Suicide Prevention Resource Center and the American Foundation for Suicide Prevention Best Practices Registry for Suicide Prevention.²³ Safety planning involves a collaboration between patient and physician to identify risk factors and protective factors along with crisis resources and strategies to reduce engagement in suicide behaviors.^12,22

Continue to: THE CASE

THE CASE

Based on the concerning results from the ­PHQ-9 suicide item, Emily’s physician conducted a comprehensive suicide risk assessment using both clinical interview and the C-SSRS. Emily reported that she was experiencing daily suicidal ideations due to a lack of social support and longing to be with her deceased father. She had not previously attempted suicide and had no imminent intent to commit suicide. Emily did, however, have a plan to overdose on opioid medications she had been collecting for many months. Her physician determined that Emily was at moderate risk for suicide and consulted with the clinic’s behavioral health consultant, a psychologist, to confirm a treatment plan.

After a comprehensive suicide risk assessment, determine the patient’s level of risk and follow a stepped approach to clinical care.

Emily and her physician collaboratively developed a safety plan including means reduction. Emily agreed to have her physician contact a friend to assist with safety planning, and she brought her opioid medications to the primary care clinic for disposal. Follow-up appointments were scheduled with the physician for every other week. The psychologist was available at the time of the first biweekly appointment to consult with the physician if needed. This initial appointment was focused on Emily’s suicide risk and her ability to engage in safety planning. In addition, the physician recommended that Emily schedule time with the psychologist so that she could work on her grief and depressive symptoms.

After several weeks of the biweekly appointments with both the primary care provider and the psychologist, Emily was no longer reporting suicidal ideation and she was ready to engage in coping strategies to deal with her grief and depressive symptoms.

CORRESPONDENCE
Meredith L.C. Williamson, PhD, 2900 E. 29th Street, Suite 100, Bryan, TX 77802; [email protected].

THE CASE

Emily T,* a 30-year-old woman, visited her primary care physician as follow-up to reassess her grief over the loss of her father a year earlier. Emily was her father’s primary caretaker and still lived alone in his home. Emily had a history of chronic pain and major depressive disorder and had expressed feelings of worthlessness and hopelessness about her future since her father’s passing. In addition to her continuing grief response, she reported feeling worse on most days. She completed the Patient Health Questionnaire-9, and results indicated anhedonia, depressed mood, psychomotor retardation, hypersomnia, decreased appetite, decreased concentration, and thoughts that she would be better off dead.

• HOW WOULD YOU PROCEED WITH THIS PATIENT?

* The patient’s name has been changed to protect her identity.

In the United States, 1 suicide occurs on average every 12 minutes; lifetime prevalence of suicide attempts ranges from 1.9% to 8.7%.¹ Suicide is the 10th overall cause of death in the United States, and it is the second leading cause of death for adults 18 to 34 years of age.² In one study, nearly half of suicide victims had contact with primary care providers within 1 month of their suicide.³ Unfortunately, additional research suggests that primary care physicians appropriately screen for suicide in fewer than 40% of patient encounters.^4,5

Suicide is defined as “death caused by self-directed injurious behavior with any intent to die as a result of the behavior.”⁶ When screening for suicide, be aware of the many terms related to suicide evaluation (TABLE 1⁶). Be mindful, too, of the differences between suicidal and nonsuicidal ideation (death wish); the continuum of such thoughts ranges from those that lead to suicide to those that do not.

SUICIDE SCREENING RECOMMENDATIONS VARY

Although most health care providers would agree that intervening with a suicidal patient first requires competence in assessing suicide risk, regulating bodies differ on the use of routine screening and on appropriate screening tools for primary care. The Joint Commission recommends assessing suicide risk with all primary care patients,⁷ while the US Preventive Services Tasks Force (USPSTF) advises against universal suicide screening in primary care⁸ due to insufficient evidence that its benefit outweighs potential harm (TABLE 2^7-12). Instead, the USPSTF recommends screening primary care patients with known mental health disorders, recent inpatient psychiatric hospitalization, prior suicide or self-harm attempts, or increased emotional distress.⁸ USPSTF does support screening for depression with routine mental health measures that include items assessing suicidality.^8,13,14 The American Academy of Family Physicians supports the recommendations by USPSTF.¹³

When screening for suicide, a comprehensive suicide risk assessment is recommended by both the Joint Commission and USPSTF.^7,8 A comprehensive suicide risk assessment has 4 components: (1) identification of current suicide risk factors, (2) identification of protective factors, (3) inquiry about suicidal ideation, intent, and plan, and (4) primary care practitioner judgment of risk level and plan for clinical intervention.^9-11

Take into account both risks and protective factors

Unfortunately, there is no “typical” description of a patient at risk for suicide and no validated models to predict suicide risk.^8,10 A multitude of factors, both individual and societal, can increase or reduce risk of suicide.^11,15 Each patient’s unique history includes risk factors for suicide including precipitating events (eg, job loss, termination of a relationship, death of a loved one) and protective factors that may be evaluated to determine overall risk for suicide (TABLE 3^8,10,11,15). According to the Centers for Disease Control and Prevention (CDC), there are several warning signs for patients who may be at greater risk for suicide: isolation, increased anxiety or anger, obtaining lethal means (eg, guns, knives, ropes), frequent mood swings, sleep changes, feeling trapped or in pain, increased substance use, discussing plans for death or wishes of death, and feeling like a burden.¹⁶

CHOOSING FROM AMONG SUICIDE SCREENING TOOLS

Brief mental health screening tools such as the Patient Health Questionnaire-9 (PHQ-9) are commonly used as primary screening tools for suicidal ideation.¹⁷ However, to attain a fuller understanding of a patient’s suicidality, select a screening tool that specifically focuses on suicidal ideation, intent, or plan, and then interview the patient (TABLE 4^10,11,15).

Continue to: Several screening tools...

Several screening tools are available for exploring a patient’s suicidality. Unfortunately, most of them are supported by limited evidence of effectiveness in identifying suicide risk.^8-10 An exception is the well-researched and commonly used Columbia-Suicide Severity Rating Scale (C-SSRS).^18,19 In a comparative study conducted at 2 primary care clinics, researchers found that the suicide item included in the PHQ-9 provided poor sensitivity but moderate specificity (60% and 84%, respectively),²⁰ while the C-SSRS showed high sensitivity (100%) and specificity (96%-100%) in accurately identifying various suicidal self-injurious behaviors above and beyond what was identified through a structured clinical interview.²⁰ Free copies of the C-SSRS, training materials, and follow-up assessments in multiple languages can be obtained on The Columbia Lighthouse Project Web site (http://cssrs.columbia.edu/).¹⁹

RECOMMENDATIONS FOR INTERVENTION

While there is debate regarding whom to screen for suicide, the importance of intervention when a patient is revealed to be at risk is clear. After completing a comprehensive suicide risk assessment, designate the patient’s level of risk as high, moderate, or low, and follow a stepped approach to clinical care (see the Assessment and Interventions with Potentially Suicidal Patients table (page 31) at https://www.sprc.org/sites/default/files/Final%20National%20Suicide%20Prevention%20Toolkit%202.15.18%20FINAL.pdf).¹¹ Provide any patient at risk, regardless of level, with contact information for local crisis and peer support as well as national resources (National Suicide Prevention Lifeline, (800) 273-TALK (8255), https://suicidepreventionlifeline.org/; Crisis Text Line, Text HOME to 741741, https://www.crisistextline.org/).

The Columbia- Suicide Severity Rating Scale has higher sensitivity and specificity for suicide risk than the PHQ-9.

When a patient is at high risk for suicide and reports an imminent plan or intent, ensure their safety through inpatient psychiatric hospitalization and then close follow-up upon hospital discharge. First encourage voluntary hospitalization in a collaborative discussion with the patient; resort to involuntary hospitalization only if the patient resists.

What not to do. When the patient does not require immediate hospitalization, evidence recommends against contracting for patient safety via a written contract or requiring patients to verbally guarantee that they will not commit suicide upon leaving a provider’s office.²¹ Concerns about such contracts include a lack of evidence supporting their use, decreased vigilance by health care workers when such contracts are in place, and questions regarding informed consent and competence.²¹ Instead, engage a patient who is at moderate or low risk in safety planning, and meet with the patient frequently to discuss continued safety planning through close follow-up (or with a behavioral health provider if available).^10-12,22 With patients previously identified as at high risk for suicide who return from inpatient psychiatric hospitalization, continue to screen them for suicide at subsequent visits and engage them in collaborative safety planning.

Safety planning (TABLE 5¹²), also known as crisis response planning, is considered a best practice and effective suicide prevention intervention by the Suicide Prevention Resource Center and the American Foundation for Suicide Prevention Best Practices Registry for Suicide Prevention.²³ Safety planning involves a collaboration between patient and physician to identify risk factors and protective factors along with crisis resources and strategies to reduce engagement in suicide behaviors.^12,22

Continue to: THE CASE

THE CASE

Based on the concerning results from the ­PHQ-9 suicide item, Emily’s physician conducted a comprehensive suicide risk assessment using both clinical interview and the C-SSRS. Emily reported that she was experiencing daily suicidal ideations due to a lack of social support and longing to be with her deceased father. She had not previously attempted suicide and had no imminent intent to commit suicide. Emily did, however, have a plan to overdose on opioid medications she had been collecting for many months. Her physician determined that Emily was at moderate risk for suicide and consulted with the clinic’s behavioral health consultant, a psychologist, to confirm a treatment plan.

After a comprehensive suicide risk assessment, determine the patient’s level of risk and follow a stepped approach to clinical care.

Emily and her physician collaboratively developed a safety plan including means reduction. Emily agreed to have her physician contact a friend to assist with safety planning, and she brought her opioid medications to the primary care clinic for disposal. Follow-up appointments were scheduled with the physician for every other week. The psychologist was available at the time of the first biweekly appointment to consult with the physician if needed. This initial appointment was focused on Emily’s suicide risk and her ability to engage in safety planning. In addition, the physician recommended that Emily schedule time with the psychologist so that she could work on her grief and depressive symptoms.

After several weeks of the biweekly appointments with both the primary care provider and the psychologist, Emily was no longer reporting suicidal ideation and she was ready to engage in coping strategies to deal with her grief and depressive symptoms.

CORRESPONDENCE
Meredith L.C. Williamson, PhD, 2900 E. 29th Street, Suite 100, Bryan, TX 77802; [email protected].

Computer technology and artificial intelligence (AI) have come a long way in several decades:

• Between 1971 and 1996, access to the Medline database was primarily limited to university libraries and other institutions; in 1997, the database became universally available online as PubMed.¹
• In 2004, the President of the United States issued an executive order that launched a 10-year plan to put electronic health records (EHRs) in place nationwide; EHRs are now employed in nearly 9 of 10 (85.9%) medical offices.²

Over time, numerous online resources sprouted as well, including DxPlain, UpToDate, and Clinical Key, to name a few. These digital tools were impressive for their time, but many of them are now considered “old-school” AI-enabled clinical decision support.

In the past 2 to 3 years, innovative clinicians and technologists have pushed medicine into a new era that takes advantage of machine learning (ML)-enhanced diagnostic aids, software systems that predict disease progression, and advanced clinical pathways to help individualize treatment. Enthusiastic early adopters believe these resources are transforming patient care—although skeptics remain unconvinced, cautioning that they have yet to prove their worth in everyday clinical practice.

In this review, we first analyze the strengths and weaknesses of evidence supporting these tools, then propose a potential role for them in family medicine.

Machine learning takes on retinopathy

The term “artificial intelligence” has been with us for longer than a half century.³ In the broadest sense, AI refers to any computer system capable of automating a process usually performed manually by humans. But the latest innovations in AI take advantage of a subset of AI called “machine learning”: the ability of software systems to learn new functionality or insights on their own, without additional programming from human data engineers. Case in point: A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

The landmark study that started clinicians and health care executives thinking seriously about the potential role of ML in medical practice was spearheaded by ­Varun Gulshan, PhD, at Google, and associates from several medical schools.⁴ Gulshan used an artificial neural network designed to mimic the functions of the human nervous system to analyze more than 128,000 retinal images, looking for evidence of diabetic retinopathy. (See “Deciphering artificial neural networks,” for an explanation of how such networks function.⁵) The algorithm they employed was compared with the diagnostic skills of several board-certified ophthalmologists.

[polldaddy:10453606]

Continue to: Deciperhing artificial neural networks

Using an area-under-the-receiver operating curve (AUROC) as a metric, and choosing an operating point for high specificity, the algorithm generated sensitivity of 87% and 90.3% and specificity of 98.1% and 98.5% for 2 validation data sets for detecting referable retinopathy, as defined by a panel of at least 7 ophthalmologists. When AUROC was set for high sensitivity, the algorithm generated sensitivity of 97.5% and 96.1% and specificity of 93.4% and 93.9% for the 2 data sets.

These results are impressive, but the researchers used a retrospective approach in their analysis. A prospective analysis would provide stronger evidence.

That shortcoming was addressed by a pivotal clinical trial that convinced the US Food and Drug Administration (FDA) to approve the technology. Michael Abramoff, MD, PhD, at the University of Iowa Department of Ophthalmology and Visual Sciences and his associates⁶ conducted a prospective study that compared the gold standard for detecting retinopathy, the Fundus Photograph Reading Center (of the University of Wisconsin School of Medicine and Public Health), to an ML-based algorithm, the commercialized IDx-DR. The IDx-DR is a software system that is used in combination with a fundal camera to capture retinal images. The researchers found that “the AI system exceeded all pre-specified superiority endpoints at sensitivity of 87.2% ... [and] specificity of 90.7% ....”

Continue to: The FDA clearance statement...

The FDA clearance statement for this technology⁷ limits its use, emphasizing that it is intended only as a screening tool, not a stand-alone diagnostic system. Because ­IDx-DR is being used in primary care, the FDA states that patients who have a positive result should be referred to an eye care professional. The technology is contraindicated in patients who have a history of laser treatment, surgery, or injection in the eye or who have any of the following: persistent vision loss, blurred vision, floaters, previously diagnosed macular edema, severe nonproliferative retinopathy, proliferative retinopathy, radiation retinopathy, and retinal vein occlusion. It is also not intended for pregnant patients because their eye disease often progresses rapidly.

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person's risk of colorectal cancer by using age, gender, and complete blood count.

Additional caveats to keep in mind when evaluating this new technology include that, although the software can help detect retinopathy, it does not address other key issues for this patient population, including cataracts and glaucoma. The cost of the new technology also requires attention: Software must be used in conjunction with a specific retinal camera, the Topcon TRC-NW400, which is expensive (new, as much as $20,000).

IMAGE: ©GETTY IMAGES

Speaking of cost: Health care providers and insurers still question whether implementing AI-enabled systems is cost-­effective. It is too early to say definitively how AI and machine learning will have an impact on health care expenditures, because the most promising technological systems have yet to be fully implemented in hospitals and medical practices nationwide. Projections by Forbes suggest that private investment in health care AI will reach $6.6 billion by 2021; on a more confident note, an Accenture analysis predicts that the best possible application of AI might save the health care sector $150 billion annually by 2026.⁸

What role might this diabetic retinopathy technology play in family medicine? Physicians are constantly advising patients who have diabetes about the need to have a regular ophthalmic examination to check for early signs of retinopathy—advice that is often ignored. The American Academy of Ophthalmology points out that “6 out of 10 people with diabetes skip a sight-saving exam.”⁹ When a patient is screened with this type of device and found to be at high risk of eye disease, however, the advice to see an eye-care specialist might carry more weight.

Screening colonoscopy: Improving patient incentives

No responsible physician doubts the value of screening colonoscopy in patients 50 years and older, but many patients have yet to realize that the procedure just might save their life. Is there a way to incentivize resistant patients to have a colonoscopy performed? An ML-based software system that only requires access to a few readily available parameters might be the needed impetus for many patients.

Continue to: A large-scale validation...

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person’s risk of colorectal cancer by using age, gender, and complete blood count.¹⁰ This retrospective investigation analyzed more than 17,000 Kaiser Permanente patients, including 900 who already had colorectal cancer. The analysis generated a risk score for patients who did not have the malignancy to gauge their likelihood of developing it. The algorithms were more sensitive for detecting tumors of the cecum and ascending colon, and less sensitive for detection of tumors of the transverse and sigmoid colon and rectum.

To provide more definitive evidence to support the value of the software platform, a prospective study was subsequently conducted on more than 79,000 patients who had initially declined to undergo colorectal screening. The platform, called ColonFlag, was used to detect 688 patients at highest risk, who were then offered screening colonoscopy. In this subgroup, 254 agreed to the procedure; ColonFlag identified 19 malignancies (7.5%) among patients within the Maccabi Health System (Israel), and 15 more in patients outside that health system.¹¹ (In the United States, the same program is known as LGI Flag and has been cleared by the FDA.)

Although ColonFlag has the potential to reduce the incidence of colorectal cancer, other evidence-based screening modalities are highlighted in US Preventive Services Task Force guidelines, including the guaiac-based fecal occult blood test and the fecal immunochemical test.¹²

Beyond screening to applications in managing disease

The complex etiology of sepsis makes the condition difficult to treat. That complexity has also led to disagreement on the best course of management. Using an ML algorithm called an “Artificial Intelligence Clinician,” Komorowski and associates¹³ extracted data from a large data set from 2 nonoverlapping intensive care unit databases collected from US adults.The researchers’ analysis suggested a list of 48 variables that likely influence sepsis outcomes, including:

• demographics,
• Elixhauser premorbid status,
• vital signs,
• clinical laboratory data,
• intravenous fluids given, and
• vasopressors administered.

Komorowski and co-workers concluded that “… mortality was lowest in patients for whom clinicians’ actual doses matched the AI decisions. Our model provides individualized and clinically interpretable treatment decisions for sepsis that could improve patient outcomes.”

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers—blood pressure, heart rate, temperature, respiratory rate, peripheral capillary oxygen saturation (SpO₂), and age—can improve clinical outcomes in patients with severe sepsis.¹⁴ The alerts generated by the algorithm were used to guide treatment. Average length of stay was 13 days in controls, compared with 10.3 days in those evaluated with the ML algorithm. The algorithm was also associated with a 12.4% drop in in-­hospital mortality.

Continue to: Addressing challenges, tapping resources

Advances in the management of diabetic retinopathy, colorectal cancer, and sepsis are the tip of the AI iceberg. There are now ML programs to distinguish melanoma from benign nevi; to improve insulin dosing for patients with type 1 diabetes; to predict which hospital patients are most likely to end up in the intensive care unit; and to mitigate the opioid epidemic.

An ML Web page on the JAMA Network (https://sites.jamanetwork.com/machine-learning/) features a long list of published research studies, reviews, and opinion papers suggesting that the future of medicine is closely tied to innovative developments in this area. This Web page also addresses the potential use of ML in detecting lymph node metastases in breast cancer, the need to temper AI with human intelligence, the role of AI in clinical decision support, and more.

The JAMA Network also discusses a few of the challenges that still need to be overcome in developing ML tools for clinical medicine—challenges that you will want to be cognizant of as you evaluate new research in the field.

Black-box dilemma. A challenge that technologists face as they introduce new programs that have the potential to improve diagnosis, treatment, and prognosis is a phenomenon called the “black-box dilemma,” which refers to the complex data science, advanced statistics, and mathematical equations that underpin ML algorithms. These complexities make it difficult to explain the mechanism of action upon which software is based, which, in turn, makes many clinicians skeptical about its worth.

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers can improve clinical outcomes in patients with severe sepsis.

For example, the neural networks that are the backbone of the retinopathy algorithm discussed earlier might seem like voodoo science to those unfamiliar with the technology. It’s fortunate that several technology-savvy physicians have mastered these digital tools and have the teaching skills to explain them in plain-English tutorials. One such tutorial, “Understanding How Machine Learning Works,” is posted on the JAMA Network (https://sites.­jamanetwork.com/machine-learning/#multimedia). A more basic explanation was included in a recent Public Broadcasting System “Nova” episode, viewable at www.youtube.com/watch?v=xS2G0oolHpo.

Continue to: Limited analysis

Limited analysis. Another problem that plagues many ML-based algorithms is that they have been tested on only a single data set. (Typically, a data set refers to a collection of clinical parameters from a patient population.) For example, researchers developing an algorithm might collect their data from a single health care system.

Several investigators have addressed this shortcoming by testing their software on 2 completely independent patient populations. Banda and colleagues¹⁵ recently developed a software platform to improve the detection rate in familial hypercholesterolemia, a significant cause of premature cardiovascular disease and death that affects approximately 1 of every 250 people. Despite the urgency of identifying the disorder and providing potentially lifesaving treatment, only 10% of patients receive an accurate diagnosis.¹⁶ Banda and colleagues developed a deep-learning algorithm that is far more effective than the traditional screening approach now in use.

To address the generalizability of the algorithm, it was tested on EHR data from 2 independent health care systems: Stanford Health Care and Geisinger Health System. In Stanford patients, the positive predictive value of the algorithm was 88%, with a sensitivity of 75%; it identified 84% of affected patients at the highest probability threshold. In Geisinger patients, the classifier generated a positive predictive value of 85%.

The future of these technologies

AI and ML are not panaceas that will revolutionize medicine in the near future. Likewise, the digital tools discussed in this article are not going to solve multiple complex medical problems addressed during a single office visit. But physicians who ignore mounting evidence that supports these emerging technologies will be left behind by more forward-thinking colleagues.

The best possible application of AI might save the health care sector $150 billion annually by 2026, according to an economic analysis.

A recent commentary in Gastroenterology¹⁷ sums up the situation best: “It is now too conservative to suggest that CADe [computer-assisted detection] and CADx [computer-assisted diagnosis] carry the potential to revolutionize colonoscopy. The artificial intelligence revolution has already begun.”

CORRESPONDENCE
Paul Cerrato, MA, [email protected], [email protected]. John Halamka, MD, MS, [email protected].

Computer technology and artificial intelligence (AI) have come a long way in several decades:

• Between 1971 and 1996, access to the Medline database was primarily limited to university libraries and other institutions; in 1997, the database became universally available online as PubMed.¹
• In 2004, the President of the United States issued an executive order that launched a 10-year plan to put electronic health records (EHRs) in place nationwide; EHRs are now employed in nearly 9 of 10 (85.9%) medical offices.²

Over time, numerous online resources sprouted as well, including DxPlain, UpToDate, and Clinical Key, to name a few. These digital tools were impressive for their time, but many of them are now considered “old-school” AI-enabled clinical decision support.

In the past 2 to 3 years, innovative clinicians and technologists have pushed medicine into a new era that takes advantage of machine learning (ML)-enhanced diagnostic aids, software systems that predict disease progression, and advanced clinical pathways to help individualize treatment. Enthusiastic early adopters believe these resources are transforming patient care—although skeptics remain unconvinced, cautioning that they have yet to prove their worth in everyday clinical practice.

In this review, we first analyze the strengths and weaknesses of evidence supporting these tools, then propose a potential role for them in family medicine.

Machine learning takes on retinopathy

The term “artificial intelligence” has been with us for longer than a half century.³ In the broadest sense, AI refers to any computer system capable of automating a process usually performed manually by humans. But the latest innovations in AI take advantage of a subset of AI called “machine learning”: the ability of software systems to learn new functionality or insights on their own, without additional programming from human data engineers. Case in point: A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

The landmark study that started clinicians and health care executives thinking seriously about the potential role of ML in medical practice was spearheaded by ­Varun Gulshan, PhD, at Google, and associates from several medical schools.⁴ Gulshan used an artificial neural network designed to mimic the functions of the human nervous system to analyze more than 128,000 retinal images, looking for evidence of diabetic retinopathy. (See “Deciphering artificial neural networks,” for an explanation of how such networks function.⁵) The algorithm they employed was compared with the diagnostic skills of several board-certified ophthalmologists.

[polldaddy:10453606]

Continue to: Deciperhing artificial neural networks

Using an area-under-the-receiver operating curve (AUROC) as a metric, and choosing an operating point for high specificity, the algorithm generated sensitivity of 87% and 90.3% and specificity of 98.1% and 98.5% for 2 validation data sets for detecting referable retinopathy, as defined by a panel of at least 7 ophthalmologists. When AUROC was set for high sensitivity, the algorithm generated sensitivity of 97.5% and 96.1% and specificity of 93.4% and 93.9% for the 2 data sets.

These results are impressive, but the researchers used a retrospective approach in their analysis. A prospective analysis would provide stronger evidence.

That shortcoming was addressed by a pivotal clinical trial that convinced the US Food and Drug Administration (FDA) to approve the technology. Michael Abramoff, MD, PhD, at the University of Iowa Department of Ophthalmology and Visual Sciences and his associates⁶ conducted a prospective study that compared the gold standard for detecting retinopathy, the Fundus Photograph Reading Center (of the University of Wisconsin School of Medicine and Public Health), to an ML-based algorithm, the commercialized IDx-DR. The IDx-DR is a software system that is used in combination with a fundal camera to capture retinal images. The researchers found that “the AI system exceeded all pre-specified superiority endpoints at sensitivity of 87.2% ... [and] specificity of 90.7% ....”

Continue to: The FDA clearance statement...

The FDA clearance statement for this technology⁷ limits its use, emphasizing that it is intended only as a screening tool, not a stand-alone diagnostic system. Because ­IDx-DR is being used in primary care, the FDA states that patients who have a positive result should be referred to an eye care professional. The technology is contraindicated in patients who have a history of laser treatment, surgery, or injection in the eye or who have any of the following: persistent vision loss, blurred vision, floaters, previously diagnosed macular edema, severe nonproliferative retinopathy, proliferative retinopathy, radiation retinopathy, and retinal vein occlusion. It is also not intended for pregnant patients because their eye disease often progresses rapidly.

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person's risk of colorectal cancer by using age, gender, and complete blood count.

Additional caveats to keep in mind when evaluating this new technology include that, although the software can help detect retinopathy, it does not address other key issues for this patient population, including cataracts and glaucoma. The cost of the new technology also requires attention: Software must be used in conjunction with a specific retinal camera, the Topcon TRC-NW400, which is expensive (new, as much as $20,000).

IMAGE: ©GETTY IMAGES

Speaking of cost: Health care providers and insurers still question whether implementing AI-enabled systems is cost-­effective. It is too early to say definitively how AI and machine learning will have an impact on health care expenditures, because the most promising technological systems have yet to be fully implemented in hospitals and medical practices nationwide. Projections by Forbes suggest that private investment in health care AI will reach $6.6 billion by 2021; on a more confident note, an Accenture analysis predicts that the best possible application of AI might save the health care sector $150 billion annually by 2026.⁸

What role might this diabetic retinopathy technology play in family medicine? Physicians are constantly advising patients who have diabetes about the need to have a regular ophthalmic examination to check for early signs of retinopathy—advice that is often ignored. The American Academy of Ophthalmology points out that “6 out of 10 people with diabetes skip a sight-saving exam.”⁹ When a patient is screened with this type of device and found to be at high risk of eye disease, however, the advice to see an eye-care specialist might carry more weight.

Screening colonoscopy: Improving patient incentives

No responsible physician doubts the value of screening colonoscopy in patients 50 years and older, but many patients have yet to realize that the procedure just might save their life. Is there a way to incentivize resistant patients to have a colonoscopy performed? An ML-based software system that only requires access to a few readily available parameters might be the needed impetus for many patients.

Continue to: A large-scale validation...

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person’s risk of colorectal cancer by using age, gender, and complete blood count.¹⁰ This retrospective investigation analyzed more than 17,000 Kaiser Permanente patients, including 900 who already had colorectal cancer. The analysis generated a risk score for patients who did not have the malignancy to gauge their likelihood of developing it. The algorithms were more sensitive for detecting tumors of the cecum and ascending colon, and less sensitive for detection of tumors of the transverse and sigmoid colon and rectum.

To provide more definitive evidence to support the value of the software platform, a prospective study was subsequently conducted on more than 79,000 patients who had initially declined to undergo colorectal screening. The platform, called ColonFlag, was used to detect 688 patients at highest risk, who were then offered screening colonoscopy. In this subgroup, 254 agreed to the procedure; ColonFlag identified 19 malignancies (7.5%) among patients within the Maccabi Health System (Israel), and 15 more in patients outside that health system.¹¹ (In the United States, the same program is known as LGI Flag and has been cleared by the FDA.)

Although ColonFlag has the potential to reduce the incidence of colorectal cancer, other evidence-based screening modalities are highlighted in US Preventive Services Task Force guidelines, including the guaiac-based fecal occult blood test and the fecal immunochemical test.¹²

Beyond screening to applications in managing disease

The complex etiology of sepsis makes the condition difficult to treat. That complexity has also led to disagreement on the best course of management. Using an ML algorithm called an “Artificial Intelligence Clinician,” Komorowski and associates¹³ extracted data from a large data set from 2 nonoverlapping intensive care unit databases collected from US adults.The researchers’ analysis suggested a list of 48 variables that likely influence sepsis outcomes, including:

• demographics,
• Elixhauser premorbid status,
• vital signs,
• clinical laboratory data,
• intravenous fluids given, and
• vasopressors administered.

Komorowski and co-workers concluded that “… mortality was lowest in patients for whom clinicians’ actual doses matched the AI decisions. Our model provides individualized and clinically interpretable treatment decisions for sepsis that could improve patient outcomes.”

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers—blood pressure, heart rate, temperature, respiratory rate, peripheral capillary oxygen saturation (SpO₂), and age—can improve clinical outcomes in patients with severe sepsis.¹⁴ The alerts generated by the algorithm were used to guide treatment. Average length of stay was 13 days in controls, compared with 10.3 days in those evaluated with the ML algorithm. The algorithm was also associated with a 12.4% drop in in-­hospital mortality.

Continue to: Addressing challenges, tapping resources

Advances in the management of diabetic retinopathy, colorectal cancer, and sepsis are the tip of the AI iceberg. There are now ML programs to distinguish melanoma from benign nevi; to improve insulin dosing for patients with type 1 diabetes; to predict which hospital patients are most likely to end up in the intensive care unit; and to mitigate the opioid epidemic.

An ML Web page on the JAMA Network (https://sites.jamanetwork.com/machine-learning/) features a long list of published research studies, reviews, and opinion papers suggesting that the future of medicine is closely tied to innovative developments in this area. This Web page also addresses the potential use of ML in detecting lymph node metastases in breast cancer, the need to temper AI with human intelligence, the role of AI in clinical decision support, and more.

The JAMA Network also discusses a few of the challenges that still need to be overcome in developing ML tools for clinical medicine—challenges that you will want to be cognizant of as you evaluate new research in the field.

Black-box dilemma. A challenge that technologists face as they introduce new programs that have the potential to improve diagnosis, treatment, and prognosis is a phenomenon called the “black-box dilemma,” which refers to the complex data science, advanced statistics, and mathematical equations that underpin ML algorithms. These complexities make it difficult to explain the mechanism of action upon which software is based, which, in turn, makes many clinicians skeptical about its worth.

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers can improve clinical outcomes in patients with severe sepsis.

For example, the neural networks that are the backbone of the retinopathy algorithm discussed earlier might seem like voodoo science to those unfamiliar with the technology. It’s fortunate that several technology-savvy physicians have mastered these digital tools and have the teaching skills to explain them in plain-English tutorials. One such tutorial, “Understanding How Machine Learning Works,” is posted on the JAMA Network (https://sites.­jamanetwork.com/machine-learning/#multimedia). A more basic explanation was included in a recent Public Broadcasting System “Nova” episode, viewable at www.youtube.com/watch?v=xS2G0oolHpo.

Continue to: Limited analysis

Limited analysis. Another problem that plagues many ML-based algorithms is that they have been tested on only a single data set. (Typically, a data set refers to a collection of clinical parameters from a patient population.) For example, researchers developing an algorithm might collect their data from a single health care system.

Several investigators have addressed this shortcoming by testing their software on 2 completely independent patient populations. Banda and colleagues¹⁵ recently developed a software platform to improve the detection rate in familial hypercholesterolemia, a significant cause of premature cardiovascular disease and death that affects approximately 1 of every 250 people. Despite the urgency of identifying the disorder and providing potentially lifesaving treatment, only 10% of patients receive an accurate diagnosis.¹⁶ Banda and colleagues developed a deep-learning algorithm that is far more effective than the traditional screening approach now in use.

To address the generalizability of the algorithm, it was tested on EHR data from 2 independent health care systems: Stanford Health Care and Geisinger Health System. In Stanford patients, the positive predictive value of the algorithm was 88%, with a sensitivity of 75%; it identified 84% of affected patients at the highest probability threshold. In Geisinger patients, the classifier generated a positive predictive value of 85%.

The future of these technologies

AI and ML are not panaceas that will revolutionize medicine in the near future. Likewise, the digital tools discussed in this article are not going to solve multiple complex medical problems addressed during a single office visit. But physicians who ignore mounting evidence that supports these emerging technologies will be left behind by more forward-thinking colleagues.

The best possible application of AI might save the health care sector $150 billion annually by 2026, according to an economic analysis.

A recent commentary in Gastroenterology¹⁷ sums up the situation best: “It is now too conservative to suggest that CADe [computer-assisted detection] and CADx [computer-assisted diagnosis] carry the potential to revolutionize colonoscopy. The artificial intelligence revolution has already begun.”

CORRESPONDENCE
Paul Cerrato, MA, [email protected], [email protected]. John Halamka, MD, MS, [email protected].

Computer technology and artificial intelligence (AI) have come a long way in several decades:

• Between 1971 and 1996, access to the Medline database was primarily limited to university libraries and other institutions; in 1997, the database became universally available online as PubMed.¹
• In 2004, the President of the United States issued an executive order that launched a 10-year plan to put electronic health records (EHRs) in place nationwide; EHRs are now employed in nearly 9 of 10 (85.9%) medical offices.²

Over time, numerous online resources sprouted as well, including DxPlain, UpToDate, and Clinical Key, to name a few. These digital tools were impressive for their time, but many of them are now considered “old-school” AI-enabled clinical decision support.

In the past 2 to 3 years, innovative clinicians and technologists have pushed medicine into a new era that takes advantage of machine learning (ML)-enhanced diagnostic aids, software systems that predict disease progression, and advanced clinical pathways to help individualize treatment. Enthusiastic early adopters believe these resources are transforming patient care—although skeptics remain unconvinced, cautioning that they have yet to prove their worth in everyday clinical practice.

In this review, we first analyze the strengths and weaknesses of evidence supporting these tools, then propose a potential role for them in family medicine.

Machine learning takes on retinopathy

The term “artificial intelligence” has been with us for longer than a half century.³ In the broadest sense, AI refers to any computer system capable of automating a process usually performed manually by humans. But the latest innovations in AI take advantage of a subset of AI called “machine learning”: the ability of software systems to learn new functionality or insights on their own, without additional programming from human data engineers. Case in point: A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

A software platform has been developed that is capable of diagnosing or screening for diabetic retinopathy without the involvement of an experienced ophthalmologist.

The landmark study that started clinicians and health care executives thinking seriously about the potential role of ML in medical practice was spearheaded by ­Varun Gulshan, PhD, at Google, and associates from several medical schools.⁴ Gulshan used an artificial neural network designed to mimic the functions of the human nervous system to analyze more than 128,000 retinal images, looking for evidence of diabetic retinopathy. (See “Deciphering artificial neural networks,” for an explanation of how such networks function.⁵) The algorithm they employed was compared with the diagnostic skills of several board-certified ophthalmologists.

[polldaddy:10453606]

Continue to: Deciperhing artificial neural networks

Using an area-under-the-receiver operating curve (AUROC) as a metric, and choosing an operating point for high specificity, the algorithm generated sensitivity of 87% and 90.3% and specificity of 98.1% and 98.5% for 2 validation data sets for detecting referable retinopathy, as defined by a panel of at least 7 ophthalmologists. When AUROC was set for high sensitivity, the algorithm generated sensitivity of 97.5% and 96.1% and specificity of 93.4% and 93.9% for the 2 data sets.

These results are impressive, but the researchers used a retrospective approach in their analysis. A prospective analysis would provide stronger evidence.

That shortcoming was addressed by a pivotal clinical trial that convinced the US Food and Drug Administration (FDA) to approve the technology. Michael Abramoff, MD, PhD, at the University of Iowa Department of Ophthalmology and Visual Sciences and his associates⁶ conducted a prospective study that compared the gold standard for detecting retinopathy, the Fundus Photograph Reading Center (of the University of Wisconsin School of Medicine and Public Health), to an ML-based algorithm, the commercialized IDx-DR. The IDx-DR is a software system that is used in combination with a fundal camera to capture retinal images. The researchers found that “the AI system exceeded all pre-specified superiority endpoints at sensitivity of 87.2% ... [and] specificity of 90.7% ....”

Continue to: The FDA clearance statement...

The FDA clearance statement for this technology⁷ limits its use, emphasizing that it is intended only as a screening tool, not a stand-alone diagnostic system. Because ­IDx-DR is being used in primary care, the FDA states that patients who have a positive result should be referred to an eye care professional. The technology is contraindicated in patients who have a history of laser treatment, surgery, or injection in the eye or who have any of the following: persistent vision loss, blurred vision, floaters, previously diagnosed macular edema, severe nonproliferative retinopathy, proliferative retinopathy, radiation retinopathy, and retinal vein occlusion. It is also not intended for pregnant patients because their eye disease often progresses rapidly.

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person's risk of colorectal cancer by using age, gender, and complete blood count.

Additional caveats to keep in mind when evaluating this new technology include that, although the software can help detect retinopathy, it does not address other key issues for this patient population, including cataracts and glaucoma. The cost of the new technology also requires attention: Software must be used in conjunction with a specific retinal camera, the Topcon TRC-NW400, which is expensive (new, as much as $20,000).

IMAGE: ©GETTY IMAGES

Speaking of cost: Health care providers and insurers still question whether implementing AI-enabled systems is cost-­effective. It is too early to say definitively how AI and machine learning will have an impact on health care expenditures, because the most promising technological systems have yet to be fully implemented in hospitals and medical practices nationwide. Projections by Forbes suggest that private investment in health care AI will reach $6.6 billion by 2021; on a more confident note, an Accenture analysis predicts that the best possible application of AI might save the health care sector $150 billion annually by 2026.⁸

What role might this diabetic retinopathy technology play in family medicine? Physicians are constantly advising patients who have diabetes about the need to have a regular ophthalmic examination to check for early signs of retinopathy—advice that is often ignored. The American Academy of Ophthalmology points out that “6 out of 10 people with diabetes skip a sight-saving exam.”⁹ When a patient is screened with this type of device and found to be at high risk of eye disease, however, the advice to see an eye-care specialist might carry more weight.

Screening colonoscopy: Improving patient incentives

No responsible physician doubts the value of screening colonoscopy in patients 50 years and older, but many patients have yet to realize that the procedure just might save their life. Is there a way to incentivize resistant patients to have a colonoscopy performed? An ML-based software system that only requires access to a few readily available parameters might be the needed impetus for many patients.

Continue to: A large-scale validation...

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person’s risk of colorectal cancer by using age, gender, and complete blood count.¹⁰ This retrospective investigation analyzed more than 17,000 Kaiser Permanente patients, including 900 who already had colorectal cancer. The analysis generated a risk score for patients who did not have the malignancy to gauge their likelihood of developing it. The algorithms were more sensitive for detecting tumors of the cecum and ascending colon, and less sensitive for detection of tumors of the transverse and sigmoid colon and rectum.

To provide more definitive evidence to support the value of the software platform, a prospective study was subsequently conducted on more than 79,000 patients who had initially declined to undergo colorectal screening. The platform, called ColonFlag, was used to detect 688 patients at highest risk, who were then offered screening colonoscopy. In this subgroup, 254 agreed to the procedure; ColonFlag identified 19 malignancies (7.5%) among patients within the Maccabi Health System (Israel), and 15 more in patients outside that health system.¹¹ (In the United States, the same program is known as LGI Flag and has been cleared by the FDA.)

Although ColonFlag has the potential to reduce the incidence of colorectal cancer, other evidence-based screening modalities are highlighted in US Preventive Services Task Force guidelines, including the guaiac-based fecal occult blood test and the fecal immunochemical test.¹²

Beyond screening to applications in managing disease

The complex etiology of sepsis makes the condition difficult to treat. That complexity has also led to disagreement on the best course of management. Using an ML algorithm called an “Artificial Intelligence Clinician,” Komorowski and associates¹³ extracted data from a large data set from 2 nonoverlapping intensive care unit databases collected from US adults.The researchers’ analysis suggested a list of 48 variables that likely influence sepsis outcomes, including:

• demographics,
• Elixhauser premorbid status,
• vital signs,
• clinical laboratory data,
• intravenous fluids given, and
• vasopressors administered.

Komorowski and co-workers concluded that “… mortality was lowest in patients for whom clinicians’ actual doses matched the AI decisions. Our model provides individualized and clinically interpretable treatment decisions for sepsis that could improve patient outcomes.”

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers—blood pressure, heart rate, temperature, respiratory rate, peripheral capillary oxygen saturation (SpO₂), and age—can improve clinical outcomes in patients with severe sepsis.¹⁴ The alerts generated by the algorithm were used to guide treatment. Average length of stay was 13 days in controls, compared with 10.3 days in those evaluated with the ML algorithm. The algorithm was also associated with a 12.4% drop in in-­hospital mortality.

Continue to: Addressing challenges, tapping resources

Advances in the management of diabetic retinopathy, colorectal cancer, and sepsis are the tip of the AI iceberg. There are now ML programs to distinguish melanoma from benign nevi; to improve insulin dosing for patients with type 1 diabetes; to predict which hospital patients are most likely to end up in the intensive care unit; and to mitigate the opioid epidemic.

An ML Web page on the JAMA Network (https://sites.jamanetwork.com/machine-learning/) features a long list of published research studies, reviews, and opinion papers suggesting that the future of medicine is closely tied to innovative developments in this area. This Web page also addresses the potential use of ML in detecting lymph node metastases in breast cancer, the need to temper AI with human intelligence, the role of AI in clinical decision support, and more.

The JAMA Network also discusses a few of the challenges that still need to be overcome in developing ML tools for clinical medicine—challenges that you will want to be cognizant of as you evaluate new research in the field.

Black-box dilemma. A challenge that technologists face as they introduce new programs that have the potential to improve diagnosis, treatment, and prognosis is a phenomenon called the “black-box dilemma,” which refers to the complex data science, advanced statistics, and mathematical equations that underpin ML algorithms. These complexities make it difficult to explain the mechanism of action upon which software is based, which, in turn, makes many clinicians skeptical about its worth.

A randomized clinical trial has found that an ML program that uses only 6 common clinical markers can improve clinical outcomes in patients with severe sepsis.

For example, the neural networks that are the backbone of the retinopathy algorithm discussed earlier might seem like voodoo science to those unfamiliar with the technology. It’s fortunate that several technology-savvy physicians have mastered these digital tools and have the teaching skills to explain them in plain-English tutorials. One such tutorial, “Understanding How Machine Learning Works,” is posted on the JAMA Network (https://sites.­jamanetwork.com/machine-learning/#multimedia). A more basic explanation was included in a recent Public Broadcasting System “Nova” episode, viewable at www.youtube.com/watch?v=xS2G0oolHpo.

Continue to: Limited analysis

Limited analysis. Another problem that plagues many ML-based algorithms is that they have been tested on only a single data set. (Typically, a data set refers to a collection of clinical parameters from a patient population.) For example, researchers developing an algorithm might collect their data from a single health care system.

Several investigators have addressed this shortcoming by testing their software on 2 completely independent patient populations. Banda and colleagues¹⁵ recently developed a software platform to improve the detection rate in familial hypercholesterolemia, a significant cause of premature cardiovascular disease and death that affects approximately 1 of every 250 people. Despite the urgency of identifying the disorder and providing potentially lifesaving treatment, only 10% of patients receive an accurate diagnosis.¹⁶ Banda and colleagues developed a deep-learning algorithm that is far more effective than the traditional screening approach now in use.

To address the generalizability of the algorithm, it was tested on EHR data from 2 independent health care systems: Stanford Health Care and Geisinger Health System. In Stanford patients, the positive predictive value of the algorithm was 88%, with a sensitivity of 75%; it identified 84% of affected patients at the highest probability threshold. In Geisinger patients, the classifier generated a positive predictive value of 85%.

The future of these technologies

AI and ML are not panaceas that will revolutionize medicine in the near future. Likewise, the digital tools discussed in this article are not going to solve multiple complex medical problems addressed during a single office visit. But physicians who ignore mounting evidence that supports these emerging technologies will be left behind by more forward-thinking colleagues.

The best possible application of AI might save the health care sector $150 billion annually by 2026, according to an economic analysis.

A recent commentary in Gastroenterology¹⁷ sums up the situation best: “It is now too conservative to suggest that CADe [computer-assisted detection] and CADx [computer-assisted diagnosis] carry the potential to revolutionize colonoscopy. The artificial intelligence revolution has already begun.”

CORRESPONDENCE
Paul Cerrato, MA, [email protected], [email protected]. John Halamka, MD, MS, [email protected].

Sleep vs. Netflix: the eternal struggle

Ladies and gentlemen, welcome to Livin’ on the MDedge World Championship Boxing! Tonight, we bring you a classic match-up in the endless battle for your valuable time.

jackscoldsweat/Getty Images

In the red corner, weighing in at a muscular 8 hours, is the defending champion: a good night’s sleep! And now for the challenger in the blue corner, coming in at a strong “just one more episode, I promise,” it’s binge watching!

Oh, sleep opens the match strong: According to a survey from the American Academy of Sleep Medicine, U.S. adults rank sleep as their second-most important priority, with only family beating it out. My goodness, that is a strong opening offensive.

But wait, binge watching is countering! According to the very same survey, 88% of Americans have admitted that they’d lost sleep because they’d stayed up late to watch extra episodes of a TV show or streaming series, a rate that rises to 95% in people aged 18-44 years. Oh dear, sleep looks like it’s in trouble.

Hang on, what’s binge watching doing? It’s unleashing a quick barrage of attacks: 72% of men aged 18-34 reported delaying sleep for video games, two-thirds of U.S. adults reported losing sleep to read a book, and nearly 60% of adults delayed sleep to watch sports. We feel slightly conflicted about our metaphor choice now.

And with a final haymaker from “guess I’ll watch ‘The Office’ for a sixth time,” binge watching has defeated the defending champion! Be sure to tune in next week, when alcohol takes on common sense. A true fight for the ages there.
 

Lead us not into temptation

Can anyone resist the temptation of binge watching? Can no one swim against the sleep-depriving, show-streaming current? Is resistance to an “Orange Is the New Black” bender futile?

spaxiax/Getty Images

University of Wyoming researchers say there’s hope. Those who would sleep svelte and sound in a world of streaming services and Krispy Kreme must plan ahead to tame temptation.

Proactive temptation management begins long before those chocolate iced glazed with sprinkles appear at the nurses’ station. Planning your response ahead of time increases the odds that the first episode of “Stranger Things” is also the evening’s last episode.

Using psychology’s human lab mice – undergraduate students – the researchers tested five temptation-proofing self-control strategies.

The first strategy: situation selection. If “Game of Thrones” is on in the den, avoid the room as if it were an unmucked House Lannister horse stall. Second: situation modification. Is your spouse hotboxing GoT on an iPad next to you in the bed? Politely suggest that GoT is even better when viewed on the living room sofa.

The third strategy: distraction. Enjoy the wholesome snap of a Finn Crisp while your coworkers destroy those Krispy Kremes like Daenerys leveling King’s Landing. Fourth: reappraisal. Tell yourself that season 2 of “Ozark” can’t surpass season 1, and will simply swindle you of your precious time. And fifth, the Nancy-Reagan, temptation-resistance classic: response inhibition. When offered the narcotic that is “Breaking Bad,” just say no!

Which temptation strategies worked best?

Planning ahead with one through four led fewer Cowboy State undergrads into temptation.

As for responding in the moment? Well, the Krispy Kremes would’ve never lasted past season 2 of “The Great British Baking Show.”
 

Stuck between a tongue and a hard place

There once was a 7-year-old boy who loved grape juice. He loved grape juice so much that he didn’t want to waste any after drinking a bottle of the stuff.

Shablon/Getty Images

To get every last drop, he tried to use his tongue to lick the inside of a grape juice bottle. One particular bottle, however, was evil and had other plans. It grabbed his tongue and wouldn’t let go, even after his mother tried to help him.

She took him to the great healing wizards at Auf der Bult Children’s Hospital in Hannover, Germany – which is quite surprising, because they live in New Jersey. [Just kidding, they’re from Hannover – just checking to see if you’re paying attention.]

When their magic wands didn’t work, doctors at the hospital mildly sedated the boy with midazolam and esketamine and then advanced a 70-mm plastic button cannula between the neck of the bottle and his tongue, hoping to release the presumed vacuum. No such luck.

It was at that point that the greatest of all the wizards, Dr. Christoph Eich, a pediatric anesthesiologist at the hospital, remembered having a similar problem with a particularly villainous bottle of “grape juice” during his magical training days some 20 years earlier.

The solution then, he discovered, was to connect the cannula to a syringe and inject air into the bottle to produce positive pressure and force out the foreign object.

Dr. Eich’s reinvention of BPAP (bottle positive airway pressure) worked on the child, who, once the purple discoloration of his tongue faded after 3 days, was none the worse for wear and lived happily ever after.

We’re just wondering if the good doctor told the child’s mother that the original situation involved a bottle of wine that couldn’t be opened because no one had a corkscrew. Well, maybe she reads the European Journal of Anaesthesiology.

Sleep vs. Netflix: the eternal struggle

Ladies and gentlemen, welcome to Livin’ on the MDedge World Championship Boxing! Tonight, we bring you a classic match-up in the endless battle for your valuable time.

jackscoldsweat/Getty Images

In the red corner, weighing in at a muscular 8 hours, is the defending champion: a good night’s sleep! And now for the challenger in the blue corner, coming in at a strong “just one more episode, I promise,” it’s binge watching!

Oh, sleep opens the match strong: According to a survey from the American Academy of Sleep Medicine, U.S. adults rank sleep as their second-most important priority, with only family beating it out. My goodness, that is a strong opening offensive.

But wait, binge watching is countering! According to the very same survey, 88% of Americans have admitted that they’d lost sleep because they’d stayed up late to watch extra episodes of a TV show or streaming series, a rate that rises to 95% in people aged 18-44 years. Oh dear, sleep looks like it’s in trouble.

Hang on, what’s binge watching doing? It’s unleashing a quick barrage of attacks: 72% of men aged 18-34 reported delaying sleep for video games, two-thirds of U.S. adults reported losing sleep to read a book, and nearly 60% of adults delayed sleep to watch sports. We feel slightly conflicted about our metaphor choice now.

And with a final haymaker from “guess I’ll watch ‘The Office’ for a sixth time,” binge watching has defeated the defending champion! Be sure to tune in next week, when alcohol takes on common sense. A true fight for the ages there.
 

Lead us not into temptation

Can anyone resist the temptation of binge watching? Can no one swim against the sleep-depriving, show-streaming current? Is resistance to an “Orange Is the New Black” bender futile?

spaxiax/Getty Images

University of Wyoming researchers say there’s hope. Those who would sleep svelte and sound in a world of streaming services and Krispy Kreme must plan ahead to tame temptation.

Proactive temptation management begins long before those chocolate iced glazed with sprinkles appear at the nurses’ station. Planning your response ahead of time increases the odds that the first episode of “Stranger Things” is also the evening’s last episode.

Using psychology’s human lab mice – undergraduate students – the researchers tested five temptation-proofing self-control strategies.

The first strategy: situation selection. If “Game of Thrones” is on in the den, avoid the room as if it were an unmucked House Lannister horse stall. Second: situation modification. Is your spouse hotboxing GoT on an iPad next to you in the bed? Politely suggest that GoT is even better when viewed on the living room sofa.

The third strategy: distraction. Enjoy the wholesome snap of a Finn Crisp while your coworkers destroy those Krispy Kremes like Daenerys leveling King’s Landing. Fourth: reappraisal. Tell yourself that season 2 of “Ozark” can’t surpass season 1, and will simply swindle you of your precious time. And fifth, the Nancy-Reagan, temptation-resistance classic: response inhibition. When offered the narcotic that is “Breaking Bad,” just say no!

Which temptation strategies worked best?

Planning ahead with one through four led fewer Cowboy State undergrads into temptation.

As for responding in the moment? Well, the Krispy Kremes would’ve never lasted past season 2 of “The Great British Baking Show.”
 

Stuck between a tongue and a hard place

There once was a 7-year-old boy who loved grape juice. He loved grape juice so much that he didn’t want to waste any after drinking a bottle of the stuff.

Shablon/Getty Images

To get every last drop, he tried to use his tongue to lick the inside of a grape juice bottle. One particular bottle, however, was evil and had other plans. It grabbed his tongue and wouldn’t let go, even after his mother tried to help him.

She took him to the great healing wizards at Auf der Bult Children’s Hospital in Hannover, Germany – which is quite surprising, because they live in New Jersey. [Just kidding, they’re from Hannover – just checking to see if you’re paying attention.]

When their magic wands didn’t work, doctors at the hospital mildly sedated the boy with midazolam and esketamine and then advanced a 70-mm plastic button cannula between the neck of the bottle and his tongue, hoping to release the presumed vacuum. No such luck.

It was at that point that the greatest of all the wizards, Dr. Christoph Eich, a pediatric anesthesiologist at the hospital, remembered having a similar problem with a particularly villainous bottle of “grape juice” during his magical training days some 20 years earlier.

The solution then, he discovered, was to connect the cannula to a syringe and inject air into the bottle to produce positive pressure and force out the foreign object.

Dr. Eich’s reinvention of BPAP (bottle positive airway pressure) worked on the child, who, once the purple discoloration of his tongue faded after 3 days, was none the worse for wear and lived happily ever after.

We’re just wondering if the good doctor told the child’s mother that the original situation involved a bottle of wine that couldn’t be opened because no one had a corkscrew. Well, maybe she reads the European Journal of Anaesthesiology.

Sleep vs. Netflix: the eternal struggle

Ladies and gentlemen, welcome to Livin’ on the MDedge World Championship Boxing! Tonight, we bring you a classic match-up in the endless battle for your valuable time.

jackscoldsweat/Getty Images

In the red corner, weighing in at a muscular 8 hours, is the defending champion: a good night’s sleep! And now for the challenger in the blue corner, coming in at a strong “just one more episode, I promise,” it’s binge watching!

Oh, sleep opens the match strong: According to a survey from the American Academy of Sleep Medicine, U.S. adults rank sleep as their second-most important priority, with only family beating it out. My goodness, that is a strong opening offensive.

But wait, binge watching is countering! According to the very same survey, 88% of Americans have admitted that they’d lost sleep because they’d stayed up late to watch extra episodes of a TV show or streaming series, a rate that rises to 95% in people aged 18-44 years. Oh dear, sleep looks like it’s in trouble.

Hang on, what’s binge watching doing? It’s unleashing a quick barrage of attacks: 72% of men aged 18-34 reported delaying sleep for video games, two-thirds of U.S. adults reported losing sleep to read a book, and nearly 60% of adults delayed sleep to watch sports. We feel slightly conflicted about our metaphor choice now.

And with a final haymaker from “guess I’ll watch ‘The Office’ for a sixth time,” binge watching has defeated the defending champion! Be sure to tune in next week, when alcohol takes on common sense. A true fight for the ages there.
 

Lead us not into temptation

Can anyone resist the temptation of binge watching? Can no one swim against the sleep-depriving, show-streaming current? Is resistance to an “Orange Is the New Black” bender futile?

spaxiax/Getty Images

University of Wyoming researchers say there’s hope. Those who would sleep svelte and sound in a world of streaming services and Krispy Kreme must plan ahead to tame temptation.

Proactive temptation management begins long before those chocolate iced glazed with sprinkles appear at the nurses’ station. Planning your response ahead of time increases the odds that the first episode of “Stranger Things” is also the evening’s last episode.

Using psychology’s human lab mice – undergraduate students – the researchers tested five temptation-proofing self-control strategies.

The first strategy: situation selection. If “Game of Thrones” is on in the den, avoid the room as if it were an unmucked House Lannister horse stall. Second: situation modification. Is your spouse hotboxing GoT on an iPad next to you in the bed? Politely suggest that GoT is even better when viewed on the living room sofa.

The third strategy: distraction. Enjoy the wholesome snap of a Finn Crisp while your coworkers destroy those Krispy Kremes like Daenerys leveling King’s Landing. Fourth: reappraisal. Tell yourself that season 2 of “Ozark” can’t surpass season 1, and will simply swindle you of your precious time. And fifth, the Nancy-Reagan, temptation-resistance classic: response inhibition. When offered the narcotic that is “Breaking Bad,” just say no!

Which temptation strategies worked best?

Planning ahead with one through four led fewer Cowboy State undergrads into temptation.

As for responding in the moment? Well, the Krispy Kremes would’ve never lasted past season 2 of “The Great British Baking Show.”
 

Stuck between a tongue and a hard place

There once was a 7-year-old boy who loved grape juice. He loved grape juice so much that he didn’t want to waste any after drinking a bottle of the stuff.

Shablon/Getty Images

To get every last drop, he tried to use his tongue to lick the inside of a grape juice bottle. One particular bottle, however, was evil and had other plans. It grabbed his tongue and wouldn’t let go, even after his mother tried to help him.

She took him to the great healing wizards at Auf der Bult Children’s Hospital in Hannover, Germany – which is quite surprising, because they live in New Jersey. [Just kidding, they’re from Hannover – just checking to see if you’re paying attention.]

When their magic wands didn’t work, doctors at the hospital mildly sedated the boy with midazolam and esketamine and then advanced a 70-mm plastic button cannula between the neck of the bottle and his tongue, hoping to release the presumed vacuum. No such luck.

It was at that point that the greatest of all the wizards, Dr. Christoph Eich, a pediatric anesthesiologist at the hospital, remembered having a similar problem with a particularly villainous bottle of “grape juice” during his magical training days some 20 years earlier.

The solution then, he discovered, was to connect the cannula to a syringe and inject air into the bottle to produce positive pressure and force out the foreign object.

Dr. Eich’s reinvention of BPAP (bottle positive airway pressure) worked on the child, who, once the purple discoloration of his tongue faded after 3 days, was none the worse for wear and lived happily ever after.

We’re just wondering if the good doctor told the child’s mother that the original situation involved a bottle of wine that couldn’t be opened because no one had a corkscrew. Well, maybe she reads the European Journal of Anaesthesiology.

LAS VEGAS – The incidence of melanoma in the United States continues to increase, yet mortality from the disease has been stable and may even be starting to decline, according to data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

At the Skin Disease Education Foundation’s annual Las Vegas Dermatology Seminar, Laura Korb Ferris, MD, PhD, said that SEER data project 96,480 new cases of melanoma in 2019, as well as 7,230 deaths from the disease. In 2016, SEER projected 10,130 deaths from melanoma, “so we’re actually projecting a reduction in melanoma deaths,” said Dr. Ferris, director of clinical trials at the University of Pittsburgh Medical Center’s department of dermatology. She added that the death rate from melanoma in 2016 was 2.17 per 100,000 population, a reduction from 2.69 per 100,000 population in 2011, “so it looks like melanoma mortality may be stable,” or even reduced, despite an increase in melanoma incidence.

A study of SEER data between 1989 and 2009 found that melanoma incidence is increasing across all lesion thicknesses (J Natl Cancer Inst. 2015 Nov 12. doi: 10.1093/jnci/djv294). Specifically, the incidence increased most among thin lesions, but there was a smaller increased incidence of thick melanoma. “This suggests that the overall burden of disease is truly increasing, but it is primarily stemming from an increase in T1/T2 disease,” Dr. Ferris said. “This could be due in part to increased early detection.”

Improvements in melanoma-specific survival, she continued, are likely a combination of improved management of T4 disease, a shift toward detection of thinner T1/T2 melanoma, and increased detection of T1/T2 disease.

The SEER data also showed that the incidence of fatal cases of melanoma has decreased since 1989, but only in thick melanomas. This trend may indicate a modest improvement in the management of T4 tumors. “Optimistically, I think increased detection efforts are improving survival by early detection of thin but ultimately fatal melanomas,” Dr. Ferris said. “Hopefully we are finding disease earlier and we are preventing patients from progressing to these fatal T4 melanomas.”

Disparities in melanoma-specific survival also come into play. Men have poorer survival compared with women, whites have the highest survival, and non-Hispanic whites have a better survival than Hispanic whites, Dr. Ferris said, while lower rates of survival are seen in blacks and nonblack minorities, as well as among those in high poverty and those who are separated/nonmarried. Lesion type also matters. The highest survival is seen in those with superficial spreading melanoma, while lower survival is observed in those with nodular melanoma, and acral lentiginous melanoma.

Self-detection of melanoma is another strategy to consider. According to Dr. Ferris, results from multiple studies suggest that about 50% of all melanomas are detected by patients, but the ones they find tend to be thicker than the ones that clinicians detect during office visits. “It would be great if we can get that number higher than 50%,” Dr. Ferris said. “If patients really understood what melanoma is, what it looks like, and when they needed to seek medical attention, perhaps we could get that over 50% and see self-detection of thinner melanomas. That’s a very low-cost intervention.”

Targeted screening efforts that stratify by risk factors and by age “makes screening more efficient and more cost-effective,” she added. She cited one analysis, which found that clinicians need to screen 606 people and conduct 25 biopsies in order to find one melanoma. “That’s very resource intensive,” she said. “However, if you only screened people 50 or older or 65 or older, the number needed to screen goes down, and because your pretest probability is higher, your number need to biopsy goes down as well. If you factor in things like a history of atypical nevi or a personal history of melanoma, those patients are at a higher risk of developing melanoma.”

Dr. Ferris closed her presentation by noting that Australia leads other countries in melanoma prevention efforts. There, the combined incidence of skin cancer is higher than the incidence of any other type of cancer. Four decades ago, Australian health officials launched SunSmart, a series of initiatives intended to reduce skin cancer. These include implementation of policies for hat wearing and shade provision in schools and at work, availability of more effective sunscreens, inclusion of sun protection items as a tax-deductible expense for outdoor workers, increased availability since the 1980s of long-sleeved sun protective swimwear, a ban on the use of indoor tanning since 2014, provision of UV forecasts in weather, and a comprehensive program of grants for community shade structures (PLoSMed. 2019 Oct 8;16[10]:e1002932).

“One approach to melanoma prevention won’t fit all,” she concluded. “We need to focus on prevention, public education to improve knowledge and self-detection.”

Dr. Ferris disclosed that she is a consultant to and an investigator for DermTech and Scibase. She is also an investigator for Castle Biosciences.

SDEF and this news organization are owned by the same parent company. Dr. Ferris spoke during a forum on cutaneous malignancies at the meeting.

[email protected]

LAS VEGAS – The incidence of melanoma in the United States continues to increase, yet mortality from the disease has been stable and may even be starting to decline, according to data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

At the Skin Disease Education Foundation’s annual Las Vegas Dermatology Seminar, Laura Korb Ferris, MD, PhD, said that SEER data project 96,480 new cases of melanoma in 2019, as well as 7,230 deaths from the disease. In 2016, SEER projected 10,130 deaths from melanoma, “so we’re actually projecting a reduction in melanoma deaths,” said Dr. Ferris, director of clinical trials at the University of Pittsburgh Medical Center’s department of dermatology. She added that the death rate from melanoma in 2016 was 2.17 per 100,000 population, a reduction from 2.69 per 100,000 population in 2011, “so it looks like melanoma mortality may be stable,” or even reduced, despite an increase in melanoma incidence.

A study of SEER data between 1989 and 2009 found that melanoma incidence is increasing across all lesion thicknesses (J Natl Cancer Inst. 2015 Nov 12. doi: 10.1093/jnci/djv294). Specifically, the incidence increased most among thin lesions, but there was a smaller increased incidence of thick melanoma. “This suggests that the overall burden of disease is truly increasing, but it is primarily stemming from an increase in T1/T2 disease,” Dr. Ferris said. “This could be due in part to increased early detection.”

Improvements in melanoma-specific survival, she continued, are likely a combination of improved management of T4 disease, a shift toward detection of thinner T1/T2 melanoma, and increased detection of T1/T2 disease.

The SEER data also showed that the incidence of fatal cases of melanoma has decreased since 1989, but only in thick melanomas. This trend may indicate a modest improvement in the management of T4 tumors. “Optimistically, I think increased detection efforts are improving survival by early detection of thin but ultimately fatal melanomas,” Dr. Ferris said. “Hopefully we are finding disease earlier and we are preventing patients from progressing to these fatal T4 melanomas.”

Disparities in melanoma-specific survival also come into play. Men have poorer survival compared with women, whites have the highest survival, and non-Hispanic whites have a better survival than Hispanic whites, Dr. Ferris said, while lower rates of survival are seen in blacks and nonblack minorities, as well as among those in high poverty and those who are separated/nonmarried. Lesion type also matters. The highest survival is seen in those with superficial spreading melanoma, while lower survival is observed in those with nodular melanoma, and acral lentiginous melanoma.

Self-detection of melanoma is another strategy to consider. According to Dr. Ferris, results from multiple studies suggest that about 50% of all melanomas are detected by patients, but the ones they find tend to be thicker than the ones that clinicians detect during office visits. “It would be great if we can get that number higher than 50%,” Dr. Ferris said. “If patients really understood what melanoma is, what it looks like, and when they needed to seek medical attention, perhaps we could get that over 50% and see self-detection of thinner melanomas. That’s a very low-cost intervention.”

Targeted screening efforts that stratify by risk factors and by age “makes screening more efficient and more cost-effective,” she added. She cited one analysis, which found that clinicians need to screen 606 people and conduct 25 biopsies in order to find one melanoma. “That’s very resource intensive,” she said. “However, if you only screened people 50 or older or 65 or older, the number needed to screen goes down, and because your pretest probability is higher, your number need to biopsy goes down as well. If you factor in things like a history of atypical nevi or a personal history of melanoma, those patients are at a higher risk of developing melanoma.”

Dr. Ferris closed her presentation by noting that Australia leads other countries in melanoma prevention efforts. There, the combined incidence of skin cancer is higher than the incidence of any other type of cancer. Four decades ago, Australian health officials launched SunSmart, a series of initiatives intended to reduce skin cancer. These include implementation of policies for hat wearing and shade provision in schools and at work, availability of more effective sunscreens, inclusion of sun protection items as a tax-deductible expense for outdoor workers, increased availability since the 1980s of long-sleeved sun protective swimwear, a ban on the use of indoor tanning since 2014, provision of UV forecasts in weather, and a comprehensive program of grants for community shade structures (PLoSMed. 2019 Oct 8;16[10]:e1002932).

“One approach to melanoma prevention won’t fit all,” she concluded. “We need to focus on prevention, public education to improve knowledge and self-detection.”

Dr. Ferris disclosed that she is a consultant to and an investigator for DermTech and Scibase. She is also an investigator for Castle Biosciences.

SDEF and this news organization are owned by the same parent company. Dr. Ferris spoke during a forum on cutaneous malignancies at the meeting.

[email protected]

LAS VEGAS – The incidence of melanoma in the United States continues to increase, yet mortality from the disease has been stable and may even be starting to decline, according to data from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program.

At the Skin Disease Education Foundation’s annual Las Vegas Dermatology Seminar, Laura Korb Ferris, MD, PhD, said that SEER data project 96,480 new cases of melanoma in 2019, as well as 7,230 deaths from the disease. In 2016, SEER projected 10,130 deaths from melanoma, “so we’re actually projecting a reduction in melanoma deaths,” said Dr. Ferris, director of clinical trials at the University of Pittsburgh Medical Center’s department of dermatology. She added that the death rate from melanoma in 2016 was 2.17 per 100,000 population, a reduction from 2.69 per 100,000 population in 2011, “so it looks like melanoma mortality may be stable,” or even reduced, despite an increase in melanoma incidence.

A study of SEER data between 1989 and 2009 found that melanoma incidence is increasing across all lesion thicknesses (J Natl Cancer Inst. 2015 Nov 12. doi: 10.1093/jnci/djv294). Specifically, the incidence increased most among thin lesions, but there was a smaller increased incidence of thick melanoma. “This suggests that the overall burden of disease is truly increasing, but it is primarily stemming from an increase in T1/T2 disease,” Dr. Ferris said. “This could be due in part to increased early detection.”

Improvements in melanoma-specific survival, she continued, are likely a combination of improved management of T4 disease, a shift toward detection of thinner T1/T2 melanoma, and increased detection of T1/T2 disease.

The SEER data also showed that the incidence of fatal cases of melanoma has decreased since 1989, but only in thick melanomas. This trend may indicate a modest improvement in the management of T4 tumors. “Optimistically, I think increased detection efforts are improving survival by early detection of thin but ultimately fatal melanomas,” Dr. Ferris said. “Hopefully we are finding disease earlier and we are preventing patients from progressing to these fatal T4 melanomas.”

Disparities in melanoma-specific survival also come into play. Men have poorer survival compared with women, whites have the highest survival, and non-Hispanic whites have a better survival than Hispanic whites, Dr. Ferris said, while lower rates of survival are seen in blacks and nonblack minorities, as well as among those in high poverty and those who are separated/nonmarried. Lesion type also matters. The highest survival is seen in those with superficial spreading melanoma, while lower survival is observed in those with nodular melanoma, and acral lentiginous melanoma.

Self-detection of melanoma is another strategy to consider. According to Dr. Ferris, results from multiple studies suggest that about 50% of all melanomas are detected by patients, but the ones they find tend to be thicker than the ones that clinicians detect during office visits. “It would be great if we can get that number higher than 50%,” Dr. Ferris said. “If patients really understood what melanoma is, what it looks like, and when they needed to seek medical attention, perhaps we could get that over 50% and see self-detection of thinner melanomas. That’s a very low-cost intervention.”

Targeted screening efforts that stratify by risk factors and by age “makes screening more efficient and more cost-effective,” she added. She cited one analysis, which found that clinicians need to screen 606 people and conduct 25 biopsies in order to find one melanoma. “That’s very resource intensive,” she said. “However, if you only screened people 50 or older or 65 or older, the number needed to screen goes down, and because your pretest probability is higher, your number need to biopsy goes down as well. If you factor in things like a history of atypical nevi or a personal history of melanoma, those patients are at a higher risk of developing melanoma.”

Dr. Ferris closed her presentation by noting that Australia leads other countries in melanoma prevention efforts. There, the combined incidence of skin cancer is higher than the incidence of any other type of cancer. Four decades ago, Australian health officials launched SunSmart, a series of initiatives intended to reduce skin cancer. These include implementation of policies for hat wearing and shade provision in schools and at work, availability of more effective sunscreens, inclusion of sun protection items as a tax-deductible expense for outdoor workers, increased availability since the 1980s of long-sleeved sun protective swimwear, a ban on the use of indoor tanning since 2014, provision of UV forecasts in weather, and a comprehensive program of grants for community shade structures (PLoSMed. 2019 Oct 8;16[10]:e1002932).

“One approach to melanoma prevention won’t fit all,” she concluded. “We need to focus on prevention, public education to improve knowledge and self-detection.”

Dr. Ferris disclosed that she is a consultant to and an investigator for DermTech and Scibase. She is also an investigator for Castle Biosciences.

SDEF and this news organization are owned by the same parent company. Dr. Ferris spoke during a forum on cutaneous malignancies at the meeting.

[email protected]

Researchers have developed models that successfully predict persistent postoperative pain (PPP) after total knee arthroplasty (TKA) two-thirds of the time. Major risk factors include pre-operative pain, sensory testing results, anxiety and anticipated pain.

“The results of this study provide some basis for the identification of patients at risk of PPP after TKA and highlight several modifiable factors that may be targeted by clinicians in an attempt to reduce the risk of developing PPP,” write the authors of the study, which appeared in the British Journal of Anaesthesia.

The authors, led by David Rice, PhD, of Auckland University of Technology, note that moderate to severe levels of PPP affect an estimated 10%-34% of patients at least 3 months after TKA surgery. “PPP adversely affects quality of life, is the most important predictor of patient dissatisfaction after TKA, and is a common reason for undergoing revision surgery.”

The researchers, who launched the study to gain insight into the risk factors that can predict PPP, recruited 300 New Zealand volunteers (average age = 69, 48% female, 92% white, average body mass index [BMI] = 31 kg/m²) to be surveyed before and after TKA surgery. They monitored pain and tracked a long list of possible risk factors including psychological traits (such as anxiety, pain catastrophizing and depression), physical traits (such as gender, BMI), and surgical traits (such as total surgery time).

At 6 months, 21% of 291 patients reported moderate to severe pain, and the percentage fell to 16% in 288 patients at 12 months.

The researchers developed two models that successfully predicted moderate-to-severe PPP.

The 6-month model relied on higher levels of preoperative pain intensity, temporal summation (a statistic that’s based on quantitative sensory testing), trait anxiety (a measure of individual anxiety level), and expected pain. It correctly predicted moderate to severe PPP 66% of the time (area under the curve [AUC] = 0.70, sensitivity = 0.72, specificity = 0.64).

The 12-month model relied on higher levels of all the risk factors except for temporal summation and correctly predicted moderate-to-severe PPP 66% of the time (AUC = 0.66, sensitivity = 0.61, specificity = 0.67).

The researchers noted that other research has linked trait anxiety and expected pain to PPP. In regard to anxiety, “cognitive behavioral interventions in the perioperative period aimed at reducing the threat value of surgery and of postoperative pain, improving patients’ coping strategies, and enhancing self-efficacy might help to reduce the risk of PPP after TKA,” the researchers write. “Furthermore, there is some evidence that anxiolytic medications can diminish perioperative anxiety and reduce APOP [acute postoperative pain] although its effects on PPP are unclear.”

Moving forward, the authors write, “strategies to minimize intraoperative nerve injury, reduce preoperative pain intensity, and address preoperative psychological factors such as expected pain and anxiety may lead to improved outcomes after TKA and should be explored.”

The Australia New Zealand College of Anesthetists and Auckland University of Technology funded the study. The study authors report no relevant disclosures.

SOURCE: Rice D et al. Br J Anaesth 2018;804-12. doi: https://doi.org/10.1016/j.bja.2018.05.070.

Researchers have developed models that successfully predict persistent postoperative pain (PPP) after total knee arthroplasty (TKA) two-thirds of the time. Major risk factors include pre-operative pain, sensory testing results, anxiety and anticipated pain.

“The results of this study provide some basis for the identification of patients at risk of PPP after TKA and highlight several modifiable factors that may be targeted by clinicians in an attempt to reduce the risk of developing PPP,” write the authors of the study, which appeared in the British Journal of Anaesthesia.

The authors, led by David Rice, PhD, of Auckland University of Technology, note that moderate to severe levels of PPP affect an estimated 10%-34% of patients at least 3 months after TKA surgery. “PPP adversely affects quality of life, is the most important predictor of patient dissatisfaction after TKA, and is a common reason for undergoing revision surgery.”

The researchers, who launched the study to gain insight into the risk factors that can predict PPP, recruited 300 New Zealand volunteers (average age = 69, 48% female, 92% white, average body mass index [BMI] = 31 kg/m²) to be surveyed before and after TKA surgery. They monitored pain and tracked a long list of possible risk factors including psychological traits (such as anxiety, pain catastrophizing and depression), physical traits (such as gender, BMI), and surgical traits (such as total surgery time).

At 6 months, 21% of 291 patients reported moderate to severe pain, and the percentage fell to 16% in 288 patients at 12 months.

The researchers developed two models that successfully predicted moderate-to-severe PPP.

The 6-month model relied on higher levels of preoperative pain intensity, temporal summation (a statistic that’s based on quantitative sensory testing), trait anxiety (a measure of individual anxiety level), and expected pain. It correctly predicted moderate to severe PPP 66% of the time (area under the curve [AUC] = 0.70, sensitivity = 0.72, specificity = 0.64).

The 12-month model relied on higher levels of all the risk factors except for temporal summation and correctly predicted moderate-to-severe PPP 66% of the time (AUC = 0.66, sensitivity = 0.61, specificity = 0.67).

The researchers noted that other research has linked trait anxiety and expected pain to PPP. In regard to anxiety, “cognitive behavioral interventions in the perioperative period aimed at reducing the threat value of surgery and of postoperative pain, improving patients’ coping strategies, and enhancing self-efficacy might help to reduce the risk of PPP after TKA,” the researchers write. “Furthermore, there is some evidence that anxiolytic medications can diminish perioperative anxiety and reduce APOP [acute postoperative pain] although its effects on PPP are unclear.”

Moving forward, the authors write, “strategies to minimize intraoperative nerve injury, reduce preoperative pain intensity, and address preoperative psychological factors such as expected pain and anxiety may lead to improved outcomes after TKA and should be explored.”

The Australia New Zealand College of Anesthetists and Auckland University of Technology funded the study. The study authors report no relevant disclosures.

SOURCE: Rice D et al. Br J Anaesth 2018;804-12. doi: https://doi.org/10.1016/j.bja.2018.05.070.

Researchers have developed models that successfully predict persistent postoperative pain (PPP) after total knee arthroplasty (TKA) two-thirds of the time. Major risk factors include pre-operative pain, sensory testing results, anxiety and anticipated pain.

“The results of this study provide some basis for the identification of patients at risk of PPP after TKA and highlight several modifiable factors that may be targeted by clinicians in an attempt to reduce the risk of developing PPP,” write the authors of the study, which appeared in the British Journal of Anaesthesia.

The authors, led by David Rice, PhD, of Auckland University of Technology, note that moderate to severe levels of PPP affect an estimated 10%-34% of patients at least 3 months after TKA surgery. “PPP adversely affects quality of life, is the most important predictor of patient dissatisfaction after TKA, and is a common reason for undergoing revision surgery.”

The researchers, who launched the study to gain insight into the risk factors that can predict PPP, recruited 300 New Zealand volunteers (average age = 69, 48% female, 92% white, average body mass index [BMI] = 31 kg/m²) to be surveyed before and after TKA surgery. They monitored pain and tracked a long list of possible risk factors including psychological traits (such as anxiety, pain catastrophizing and depression), physical traits (such as gender, BMI), and surgical traits (such as total surgery time).

At 6 months, 21% of 291 patients reported moderate to severe pain, and the percentage fell to 16% in 288 patients at 12 months.

The researchers developed two models that successfully predicted moderate-to-severe PPP.

The 6-month model relied on higher levels of preoperative pain intensity, temporal summation (a statistic that’s based on quantitative sensory testing), trait anxiety (a measure of individual anxiety level), and expected pain. It correctly predicted moderate to severe PPP 66% of the time (area under the curve [AUC] = 0.70, sensitivity = 0.72, specificity = 0.64).

The 12-month model relied on higher levels of all the risk factors except for temporal summation and correctly predicted moderate-to-severe PPP 66% of the time (AUC = 0.66, sensitivity = 0.61, specificity = 0.67).

The researchers noted that other research has linked trait anxiety and expected pain to PPP. In regard to anxiety, “cognitive behavioral interventions in the perioperative period aimed at reducing the threat value of surgery and of postoperative pain, improving patients’ coping strategies, and enhancing self-efficacy might help to reduce the risk of PPP after TKA,” the researchers write. “Furthermore, there is some evidence that anxiolytic medications can diminish perioperative anxiety and reduce APOP [acute postoperative pain] although its effects on PPP are unclear.”

Moving forward, the authors write, “strategies to minimize intraoperative nerve injury, reduce preoperative pain intensity, and address preoperative psychological factors such as expected pain and anxiety may lead to improved outcomes after TKA and should be explored.”

The Australia New Zealand College of Anesthetists and Auckland University of Technology funded the study. The study authors report no relevant disclosures.

SOURCE: Rice D et al. Br J Anaesth 2018;804-12. doi: https://doi.org/10.1016/j.bja.2018.05.070.

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A 50-year-old man presents with a 1-year history of an itchy, bumpy rash on his chest. He denies any history of similar rash and says there have been no “extraordinary changes” in his life that could have triggered this manifestation. Despite consulting various primary care providers, he has been unable to acquire either a definitive diagnosis or effective treatment.

The patient works exclusively in a climate-controlled office. Although there were no changes to laundry detergent, body soap, deodorant, or other products that might have precipitated the rash’s manifestation, he tried alternate products to see what effect they might have. Nothing beneficial came from these experiments. Similarly, the family dogs were temporarily “banished” with no improvement to his condition.

From the outset, the rash and the associated itching have been confined to the patient’s chest. No one else in his family is similarly affected.

The patient is otherwise quite well. He takes no prescription medications and denies any recent foreign travel.

EXAMINATION
The papulovesicular rash is strikingly uniform. The patient’s entire chest is covered with tiny vesicles, many with clear fluid inside. The lesions average 1.2 to 2 mm in width, and nearly all are quite palpable. Each lesion is slightly erythematous but neither warm nor tender on palpation.

Examination of the rest of the patient’s exposed skin reveals no similar lesions. His back, hands, and genitals are notably free of any such lesions.

A shave biopsy is performed, utilizing a saucerization technique, and the specimen is submitted to pathology for routine processing. The report confirms the papulovesicular nature of the lesions—but more significantly, it shows consistent acantholysis (loss of intracellular connections between keratinocytes), along with focal lymphohistiocytic infiltrates.

What’s the diagnosis?

DISCUSSION
This is a classic presentation of Grover disease, also known as transient acantholytic dermatosis (AD). While not rare, it is seen only occasionally in dermatology practices. When it does walk through the door, it is twice as likely to be seen in a male than in a female patient and less commonly seen in those with darker skin.

AD is easy enough to diagnose clinically, without biopsy, particularly in classic cases such as this one. The distribution and morphology of the rash, as well as the gender and age of the patient, are all typical of this idiopathic condition. The biopsy results, besides being consistent with AD, did serve to rule out other items in the differential (eg, bacterial folliculitis, pemphigus, and acne).

Since AD was first described in 1974 by R.W. Grover, MD, much research has been conducted to flesh out the nature of the disease, its potential causes, and possible treatment. One certainty about so-called transient AD is that most cases are far from transient—in fact, they can last for a year or more. Attempts have been made to connect AD with internal disease (eg, occult malignancy) or even mercury exposure, but these theories have not been corroborated.

Consistent treatment success has also been elusive. Most patients achieve decent relief with the use of topical steroid creams, with or without the addition of anti-inflammatory medications (eg, doxycycline). Other options include isotretinoin and psoralen plus ultraviolet A (PUVA) photochemotherapy. Fortunately, most cases eventually clear up.

TAKE-HOME LEARNING POINTS

• Grover disease, also known as transient acantholytic dermatosis (AD), usually manifests with an acute eruption of papulovesicular lesions.
• AD lesions tend to be confined to the chest and are typically pruritic.
• Clinical diagnosis is usually adequate, although biopsy, which will reveal typical findings of acantholysis, may be necessary to rule out other items in the differential.
• Treatment with topical steroids, oral doxycycline, and “tincture of time” usually suffices, but resolution may take a year or more.

A 50-year-old man presents with a 1-year history of an itchy, bumpy rash on his chest. He denies any history of similar rash and says there have been no “extraordinary changes” in his life that could have triggered this manifestation. Despite consulting various primary care providers, he has been unable to acquire either a definitive diagnosis or effective treatment.

The patient works exclusively in a climate-controlled office. Although there were no changes to laundry detergent, body soap, deodorant, or other products that might have precipitated the rash’s manifestation, he tried alternate products to see what effect they might have. Nothing beneficial came from these experiments. Similarly, the family dogs were temporarily “banished” with no improvement to his condition.

From the outset, the rash and the associated itching have been confined to the patient’s chest. No one else in his family is similarly affected.

The patient is otherwise quite well. He takes no prescription medications and denies any recent foreign travel.

EXAMINATION
The papulovesicular rash is strikingly uniform. The patient’s entire chest is covered with tiny vesicles, many with clear fluid inside. The lesions average 1.2 to 2 mm in width, and nearly all are quite palpable. Each lesion is slightly erythematous but neither warm nor tender on palpation.

Examination of the rest of the patient’s exposed skin reveals no similar lesions. His back, hands, and genitals are notably free of any such lesions.

A shave biopsy is performed, utilizing a saucerization technique, and the specimen is submitted to pathology for routine processing. The report confirms the papulovesicular nature of the lesions—but more significantly, it shows consistent acantholysis (loss of intracellular connections between keratinocytes), along with focal lymphohistiocytic infiltrates.

What’s the diagnosis?

DISCUSSION
This is a classic presentation of Grover disease, also known as transient acantholytic dermatosis (AD). While not rare, it is seen only occasionally in dermatology practices. When it does walk through the door, it is twice as likely to be seen in a male than in a female patient and less commonly seen in those with darker skin.

AD is easy enough to diagnose clinically, without biopsy, particularly in classic cases such as this one. The distribution and morphology of the rash, as well as the gender and age of the patient, are all typical of this idiopathic condition. The biopsy results, besides being consistent with AD, did serve to rule out other items in the differential (eg, bacterial folliculitis, pemphigus, and acne).

Since AD was first described in 1974 by R.W. Grover, MD, much research has been conducted to flesh out the nature of the disease, its potential causes, and possible treatment. One certainty about so-called transient AD is that most cases are far from transient—in fact, they can last for a year or more. Attempts have been made to connect AD with internal disease (eg, occult malignancy) or even mercury exposure, but these theories have not been corroborated.

Consistent treatment success has also been elusive. Most patients achieve decent relief with the use of topical steroid creams, with or without the addition of anti-inflammatory medications (eg, doxycycline). Other options include isotretinoin and psoralen plus ultraviolet A (PUVA) photochemotherapy. Fortunately, most cases eventually clear up.

TAKE-HOME LEARNING POINTS

• Grover disease, also known as transient acantholytic dermatosis (AD), usually manifests with an acute eruption of papulovesicular lesions.
• AD lesions tend to be confined to the chest and are typically pruritic.
• Clinical diagnosis is usually adequate, although biopsy, which will reveal typical findings of acantholysis, may be necessary to rule out other items in the differential.
• Treatment with topical steroids, oral doxycycline, and “tincture of time” usually suffices, but resolution may take a year or more.

A 50-year-old man presents with a 1-year history of an itchy, bumpy rash on his chest. He denies any history of similar rash and says there have been no “extraordinary changes” in his life that could have triggered this manifestation. Despite consulting various primary care providers, he has been unable to acquire either a definitive diagnosis or effective treatment.

The patient works exclusively in a climate-controlled office. Although there were no changes to laundry detergent, body soap, deodorant, or other products that might have precipitated the rash’s manifestation, he tried alternate products to see what effect they might have. Nothing beneficial came from these experiments. Similarly, the family dogs were temporarily “banished” with no improvement to his condition.

From the outset, the rash and the associated itching have been confined to the patient’s chest. No one else in his family is similarly affected.

The patient is otherwise quite well. He takes no prescription medications and denies any recent foreign travel.

EXAMINATION
The papulovesicular rash is strikingly uniform. The patient’s entire chest is covered with tiny vesicles, many with clear fluid inside. The lesions average 1.2 to 2 mm in width, and nearly all are quite palpable. Each lesion is slightly erythematous but neither warm nor tender on palpation.

Examination of the rest of the patient’s exposed skin reveals no similar lesions. His back, hands, and genitals are notably free of any such lesions.

A shave biopsy is performed, utilizing a saucerization technique, and the specimen is submitted to pathology for routine processing. The report confirms the papulovesicular nature of the lesions—but more significantly, it shows consistent acantholysis (loss of intracellular connections between keratinocytes), along with focal lymphohistiocytic infiltrates.

What’s the diagnosis?

DISCUSSION
This is a classic presentation of Grover disease, also known as transient acantholytic dermatosis (AD). While not rare, it is seen only occasionally in dermatology practices. When it does walk through the door, it is twice as likely to be seen in a male than in a female patient and less commonly seen in those with darker skin.

AD is easy enough to diagnose clinically, without biopsy, particularly in classic cases such as this one. The distribution and morphology of the rash, as well as the gender and age of the patient, are all typical of this idiopathic condition. The biopsy results, besides being consistent with AD, did serve to rule out other items in the differential (eg, bacterial folliculitis, pemphigus, and acne).

Since AD was first described in 1974 by R.W. Grover, MD, much research has been conducted to flesh out the nature of the disease, its potential causes, and possible treatment. One certainty about so-called transient AD is that most cases are far from transient—in fact, they can last for a year or more. Attempts have been made to connect AD with internal disease (eg, occult malignancy) or even mercury exposure, but these theories have not been corroborated.

Consistent treatment success has also been elusive. Most patients achieve decent relief with the use of topical steroid creams, with or without the addition of anti-inflammatory medications (eg, doxycycline). Other options include isotretinoin and psoralen plus ultraviolet A (PUVA) photochemotherapy. Fortunately, most cases eventually clear up.

TAKE-HOME LEARNING POINTS

• Grover disease, also known as transient acantholytic dermatosis (AD), usually manifests with an acute eruption of papulovesicular lesions.
• AD lesions tend to be confined to the chest and are typically pruritic.
• Clinical diagnosis is usually adequate, although biopsy, which will reveal typical findings of acantholysis, may be necessary to rule out other items in the differential.
• Treatment with topical steroids, oral doxycycline, and “tincture of time” usually suffices, but resolution may take a year or more.

The FP conducted a physical exam and noticed bilateral dorsal foot dermatitis with occasional small vesicles and lichenified papules, which was suggestive of chronic contact or irritant dermatitis. The patient’s favorite pair of boots offered another clue as to the most likely contact allergens. (The boots were leather, and leather is treated with tanning agents and dyes.) A biopsy was not performed but would be expected to show spongiosis with some degree of lichenification (thickening of the dermis)—a sign of the acute on chronic nature of this process. The diagnosis of irritant or allergic contact dermatitis was made empirically.

The differential diagnosis for rashes on the feet can be broad and includes common tinea pedis, pitted keratolysis, stasis dermatitis, psoriasis, eczemas of various types, keratoderma, and contact dermatitis.

Many patients misconstrue that materials they use every day are exempt from becoming allergens. In counseling patients about this, point out that contact allergens often arise from repeated exposure. For example, dentists often develop dental amalgam allergies, hair professionals develop hair dye allergies, and machinists commonly develop cutting oil allergies. These reactions can and do occur years into their use.

The patient was started on topical clobetasol 0.05% ointment bid for 3 weeks, which provided quick relief and cleared his feet of the patches and plaques. He continued to wear his boots until contact allergy patch testing was performed in the office over a series of 3 days. This revealed an allergy to chromium, a common leather tanning agent. The patient was advised to avoid leather products including jackets, car upholstery, and gloves. After he carefully chose different footwear without a leather insole or tongue, the patient required no further therapy and remained clear.

‌

Photos and text for Photo Rounds Friday courtesy of Jonathan Karnes, MD (copyright retained).

The FP conducted a physical exam and noticed bilateral dorsal foot dermatitis with occasional small vesicles and lichenified papules, which was suggestive of chronic contact or irritant dermatitis. The patient’s favorite pair of boots offered another clue as to the most likely contact allergens. (The boots were leather, and leather is treated with tanning agents and dyes.) A biopsy was not performed but would be expected to show spongiosis with some degree of lichenification (thickening of the dermis)—a sign of the acute on chronic nature of this process. The diagnosis of irritant or allergic contact dermatitis was made empirically.

The differential diagnosis for rashes on the feet can be broad and includes common tinea pedis, pitted keratolysis, stasis dermatitis, psoriasis, eczemas of various types, keratoderma, and contact dermatitis.

Many patients misconstrue that materials they use every day are exempt from becoming allergens. In counseling patients about this, point out that contact allergens often arise from repeated exposure. For example, dentists often develop dental amalgam allergies, hair professionals develop hair dye allergies, and machinists commonly develop cutting oil allergies. These reactions can and do occur years into their use.

The patient was started on topical clobetasol 0.05% ointment bid for 3 weeks, which provided quick relief and cleared his feet of the patches and plaques. He continued to wear his boots until contact allergy patch testing was performed in the office over a series of 3 days. This revealed an allergy to chromium, a common leather tanning agent. The patient was advised to avoid leather products including jackets, car upholstery, and gloves. After he carefully chose different footwear without a leather insole or tongue, the patient required no further therapy and remained clear.

‌

Photos and text for Photo Rounds Friday courtesy of Jonathan Karnes, MD (copyright retained).

The FP conducted a physical exam and noticed bilateral dorsal foot dermatitis with occasional small vesicles and lichenified papules, which was suggestive of chronic contact or irritant dermatitis. The patient’s favorite pair of boots offered another clue as to the most likely contact allergens. (The boots were leather, and leather is treated with tanning agents and dyes.) A biopsy was not performed but would be expected to show spongiosis with some degree of lichenification (thickening of the dermis)—a sign of the acute on chronic nature of this process. The diagnosis of irritant or allergic contact dermatitis was made empirically.

The differential diagnosis for rashes on the feet can be broad and includes common tinea pedis, pitted keratolysis, stasis dermatitis, psoriasis, eczemas of various types, keratoderma, and contact dermatitis.

Many patients misconstrue that materials they use every day are exempt from becoming allergens. In counseling patients about this, point out that contact allergens often arise from repeated exposure. For example, dentists often develop dental amalgam allergies, hair professionals develop hair dye allergies, and machinists commonly develop cutting oil allergies. These reactions can and do occur years into their use.

The patient was started on topical clobetasol 0.05% ointment bid for 3 weeks, which provided quick relief and cleared his feet of the patches and plaques. He continued to wear his boots until contact allergy patch testing was performed in the office over a series of 3 days. This revealed an allergy to chromium, a common leather tanning agent. The patient was advised to avoid leather products including jackets, car upholstery, and gloves. After he carefully chose different footwear without a leather insole or tongue, the patient required no further therapy and remained clear.

‌

Photos and text for Photo Rounds Friday courtesy of Jonathan Karnes, MD (copyright retained).