Daily hydroxyurea effective, safe for African children

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– Daily hydroxyurea treatment for sickle cell disease is feasible, safe, and effective for children in sub-Saharan Africa, according to the results of a large open-label, phase 1-2, international trial.

Andrew Bowser/MDedge News
Dr. Léon Tshilolo

Hydroxyurea was associated with reduced rates of malaria and other infections, resulting in improved survival, according to Léon Tshilolo, MD, PhD, of Centre Hospitalier Monkole in Kinshasa, the Democratic Republic of the Congo.

“Based on that data, we believe that wider access to hydroxyurea for sickle cell anemia has the potential to save millions of lives in Africa,” Dr. Tshilolo said in a press conference at the annual meeting of the American Society of Hematology.

Use of hydroxyurea has been limited in Africa because of cost, access issues, and challenges associated with laboratory monitoring, according to the researchers.

Moreover, most of the data on the efficacy of hydroxyurea come from studies conducted in the United States, Europe, and other high-income settings, said the study’s senior author Russell E. Ware, MD, PhD, of Cincinnati Children’s Hospital Center.

“Now that there’s data in an African setting, I think this will go a long way to advancing [hydroxyurea therapy] and encouraging governments, organizations, and pharmaceutical companies to bring it in,” Dr. Ware said in an interview.

In the study by Dr. Ware, Dr. Tshilolo, and their colleagues, 606 children in four sub-Saharan African countries completed a 2-month pretreatment screening phase designed to capture baseline clinical and laboratory data. The children, who were aged 1-10 years, were started at 15-20 mg/kg of hydroxyurea for 6 months, followed by escalation to the maximum tolerated dose.

With a median of 2.5 years of treatment, treated children experienced less pain and anemia, fewer cases of malaria and other infections, and lower rates of transfusions and death versus rates observed in the pretreatment screening phase of the trial.

The rate of vasoocclusive pain during hydroxyurea treatment was 44.6 events per 100 patient-years, compared with 98.3 events per 100 patient-years in the pretreatment period (incidence rate ratio, 0.45; 95% confidence interval, 0.37-0.56), according to data simultaneously published in the New England Journal of Medicine.

Malaria infection rates were 22.9 events per 100 patient-years in the hydroxyurea treatment period versus 46.9 events in the pretreatment period (IRR, 0.49; 95% CI, 0.37-0.66). Rates of nonmalaria infections were 90.0 events per 100 patient-years in the hydroxyurea treatment period versus 142.5 events per 100 patient-years in the pretreatment period (IRR, 0.62; 95% CI, 0.53-0.72).

Dr. Tshilolo said investigators were “encouraged” by the reduced infection rates, particularly in light of previous concerns that hydroxyurea could suppress the immune system and put children at risk for malaria.

Death rates were 1.1 per 100 patient-years in the hydroxyurea group and 3.6 per 100 patient-years in the pretreatment period (IR, 0.30; 95% CI, 0.10-0.88). Dose-limiting toxic events occurred in 5.1% of the children, which was below the protocol-specified threshold for safety, Dr. Tshilolo added.

Dr. Tshilolo reported grants from the National Institutes of Health/National Heart, Lung, and Blood Institute and Cincinnati Children’s Research Foundation, along with nonfinancial support from Bristol-Myers Squibb. Dr. Ware reported grants from the NIH/NHLBI and Bristol-Myers Squibb.

SOURCE: Tshilolo L et al. ASH 2018, Abstract 3.

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– Daily hydroxyurea treatment for sickle cell disease is feasible, safe, and effective for children in sub-Saharan Africa, according to the results of a large open-label, phase 1-2, international trial.

Andrew Bowser/MDedge News
Dr. Léon Tshilolo

Hydroxyurea was associated with reduced rates of malaria and other infections, resulting in improved survival, according to Léon Tshilolo, MD, PhD, of Centre Hospitalier Monkole in Kinshasa, the Democratic Republic of the Congo.

“Based on that data, we believe that wider access to hydroxyurea for sickle cell anemia has the potential to save millions of lives in Africa,” Dr. Tshilolo said in a press conference at the annual meeting of the American Society of Hematology.

Use of hydroxyurea has been limited in Africa because of cost, access issues, and challenges associated with laboratory monitoring, according to the researchers.

Moreover, most of the data on the efficacy of hydroxyurea come from studies conducted in the United States, Europe, and other high-income settings, said the study’s senior author Russell E. Ware, MD, PhD, of Cincinnati Children’s Hospital Center.

“Now that there’s data in an African setting, I think this will go a long way to advancing [hydroxyurea therapy] and encouraging governments, organizations, and pharmaceutical companies to bring it in,” Dr. Ware said in an interview.

In the study by Dr. Ware, Dr. Tshilolo, and their colleagues, 606 children in four sub-Saharan African countries completed a 2-month pretreatment screening phase designed to capture baseline clinical and laboratory data. The children, who were aged 1-10 years, were started at 15-20 mg/kg of hydroxyurea for 6 months, followed by escalation to the maximum tolerated dose.

With a median of 2.5 years of treatment, treated children experienced less pain and anemia, fewer cases of malaria and other infections, and lower rates of transfusions and death versus rates observed in the pretreatment screening phase of the trial.

The rate of vasoocclusive pain during hydroxyurea treatment was 44.6 events per 100 patient-years, compared with 98.3 events per 100 patient-years in the pretreatment period (incidence rate ratio, 0.45; 95% confidence interval, 0.37-0.56), according to data simultaneously published in the New England Journal of Medicine.

Malaria infection rates were 22.9 events per 100 patient-years in the hydroxyurea treatment period versus 46.9 events in the pretreatment period (IRR, 0.49; 95% CI, 0.37-0.66). Rates of nonmalaria infections were 90.0 events per 100 patient-years in the hydroxyurea treatment period versus 142.5 events per 100 patient-years in the pretreatment period (IRR, 0.62; 95% CI, 0.53-0.72).

Dr. Tshilolo said investigators were “encouraged” by the reduced infection rates, particularly in light of previous concerns that hydroxyurea could suppress the immune system and put children at risk for malaria.

Death rates were 1.1 per 100 patient-years in the hydroxyurea group and 3.6 per 100 patient-years in the pretreatment period (IR, 0.30; 95% CI, 0.10-0.88). Dose-limiting toxic events occurred in 5.1% of the children, which was below the protocol-specified threshold for safety, Dr. Tshilolo added.

Dr. Tshilolo reported grants from the National Institutes of Health/National Heart, Lung, and Blood Institute and Cincinnati Children’s Research Foundation, along with nonfinancial support from Bristol-Myers Squibb. Dr. Ware reported grants from the NIH/NHLBI and Bristol-Myers Squibb.

SOURCE: Tshilolo L et al. ASH 2018, Abstract 3.

 

– Daily hydroxyurea treatment for sickle cell disease is feasible, safe, and effective for children in sub-Saharan Africa, according to the results of a large open-label, phase 1-2, international trial.

Andrew Bowser/MDedge News
Dr. Léon Tshilolo

Hydroxyurea was associated with reduced rates of malaria and other infections, resulting in improved survival, according to Léon Tshilolo, MD, PhD, of Centre Hospitalier Monkole in Kinshasa, the Democratic Republic of the Congo.

“Based on that data, we believe that wider access to hydroxyurea for sickle cell anemia has the potential to save millions of lives in Africa,” Dr. Tshilolo said in a press conference at the annual meeting of the American Society of Hematology.

Use of hydroxyurea has been limited in Africa because of cost, access issues, and challenges associated with laboratory monitoring, according to the researchers.

Moreover, most of the data on the efficacy of hydroxyurea come from studies conducted in the United States, Europe, and other high-income settings, said the study’s senior author Russell E. Ware, MD, PhD, of Cincinnati Children’s Hospital Center.

“Now that there’s data in an African setting, I think this will go a long way to advancing [hydroxyurea therapy] and encouraging governments, organizations, and pharmaceutical companies to bring it in,” Dr. Ware said in an interview.

In the study by Dr. Ware, Dr. Tshilolo, and their colleagues, 606 children in four sub-Saharan African countries completed a 2-month pretreatment screening phase designed to capture baseline clinical and laboratory data. The children, who were aged 1-10 years, were started at 15-20 mg/kg of hydroxyurea for 6 months, followed by escalation to the maximum tolerated dose.

With a median of 2.5 years of treatment, treated children experienced less pain and anemia, fewer cases of malaria and other infections, and lower rates of transfusions and death versus rates observed in the pretreatment screening phase of the trial.

The rate of vasoocclusive pain during hydroxyurea treatment was 44.6 events per 100 patient-years, compared with 98.3 events per 100 patient-years in the pretreatment period (incidence rate ratio, 0.45; 95% confidence interval, 0.37-0.56), according to data simultaneously published in the New England Journal of Medicine.

Malaria infection rates were 22.9 events per 100 patient-years in the hydroxyurea treatment period versus 46.9 events in the pretreatment period (IRR, 0.49; 95% CI, 0.37-0.66). Rates of nonmalaria infections were 90.0 events per 100 patient-years in the hydroxyurea treatment period versus 142.5 events per 100 patient-years in the pretreatment period (IRR, 0.62; 95% CI, 0.53-0.72).

Dr. Tshilolo said investigators were “encouraged” by the reduced infection rates, particularly in light of previous concerns that hydroxyurea could suppress the immune system and put children at risk for malaria.

Death rates were 1.1 per 100 patient-years in the hydroxyurea group and 3.6 per 100 patient-years in the pretreatment period (IR, 0.30; 95% CI, 0.10-0.88). Dose-limiting toxic events occurred in 5.1% of the children, which was below the protocol-specified threshold for safety, Dr. Tshilolo added.

Dr. Tshilolo reported grants from the National Institutes of Health/National Heart, Lung, and Blood Institute and Cincinnati Children’s Research Foundation, along with nonfinancial support from Bristol-Myers Squibb. Dr. Ware reported grants from the NIH/NHLBI and Bristol-Myers Squibb.

SOURCE: Tshilolo L et al. ASH 2018, Abstract 3.

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Key clinical point: Daily hydroxyurea treatment in sub-Saharan African children with sickle cell disease is feasible, safe, and effective, and has the additional benefit of reducing their rates of malaria and nonmalaria infections.

Major finding: Malaria infection rates were 22.9 versus 46.9 events per 100 patient-years in the hydroxyurea treatment period and pretreatment period, respectively (incidence rate ratio, 0.49; 95% CI, 0.37-0.66).

Study details: A phase 1-2, international, open-label trial including 606 children in four sub-Saharan African countries who completed a 2-month pretreatment screening phase and went on to receive hydroxyurea.

Disclosures: Dr. Tshilolo reported grants from the National Institutes of Health/National Heart, Lung, and Blood Institute and Cincinnati Children’s Research Foundation, along with nonfinancial support from Bristol-Myers Squibb. Dr. Ware reported grants from the NIH/NHLBI and Bristol-Myers Squibb.

Source: Tshilolo L et al. ASH 2018, Abstract 3.

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Flipping the fetal hemoglobin switch reverses sickle cell symptoms

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Mon, 04/08/2019 - 09:06

SAN DIEGO – Researchers were able to “flip the switch” from the adult to fetal form of hemoglobin using autologous stem cells genetically modified to simultaneously induce the fetal form of hemoglobin and decrease sickle hemoglobin.

The advance was announced by investigators at the Dana-Farber Cancer Institute and Boston Children’s Hospital at the annual meeting of the American Society of Hematology. At 6 months of follow-up, one adult patient in the proof-of-concept study has experienced a reversal of the sickle cell phenotype, with no pain episodes or respiratory or neurologic events.

The fetal form of hemoglobin is known to be protective against the signs and symptoms of sickle cell disease, but apart from a few rare exceptions, people with the disorder begin to experience debilitating symptoms as levels of the fetal form begin to decline in early childhood and levels of the adult form of hemoglobin steadily rise.

In this video interview, Erica B. Esrick, MD, from the Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, describes the novel approach of using RNA interference to knock down a repressor that suppresses expression of gamma globin in sickle cell disease.

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SAN DIEGO – Researchers were able to “flip the switch” from the adult to fetal form of hemoglobin using autologous stem cells genetically modified to simultaneously induce the fetal form of hemoglobin and decrease sickle hemoglobin.

The advance was announced by investigators at the Dana-Farber Cancer Institute and Boston Children’s Hospital at the annual meeting of the American Society of Hematology. At 6 months of follow-up, one adult patient in the proof-of-concept study has experienced a reversal of the sickle cell phenotype, with no pain episodes or respiratory or neurologic events.

The fetal form of hemoglobin is known to be protective against the signs and symptoms of sickle cell disease, but apart from a few rare exceptions, people with the disorder begin to experience debilitating symptoms as levels of the fetal form begin to decline in early childhood and levels of the adult form of hemoglobin steadily rise.

In this video interview, Erica B. Esrick, MD, from the Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, describes the novel approach of using RNA interference to knock down a repressor that suppresses expression of gamma globin in sickle cell disease.

SAN DIEGO – Researchers were able to “flip the switch” from the adult to fetal form of hemoglobin using autologous stem cells genetically modified to simultaneously induce the fetal form of hemoglobin and decrease sickle hemoglobin.

The advance was announced by investigators at the Dana-Farber Cancer Institute and Boston Children’s Hospital at the annual meeting of the American Society of Hematology. At 6 months of follow-up, one adult patient in the proof-of-concept study has experienced a reversal of the sickle cell phenotype, with no pain episodes or respiratory or neurologic events.

The fetal form of hemoglobin is known to be protective against the signs and symptoms of sickle cell disease, but apart from a few rare exceptions, people with the disorder begin to experience debilitating symptoms as levels of the fetal form begin to decline in early childhood and levels of the adult form of hemoglobin steadily rise.

In this video interview, Erica B. Esrick, MD, from the Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, describes the novel approach of using RNA interference to knock down a repressor that suppresses expression of gamma globin in sickle cell disease.

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RELIEF: In Behçet’s, apremilast improves oral ulcers for up to 28 weeks

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– Apremilast was effective and well tolerated for up to 28 weeks for the treatment of oral ulcers in patients with active Behçet’s disease, based on findings from the randomized, placebo-controlled, phase 3 RELIEF trial.

At baseline, mean oral ulcer counts were 4.2 in 104 patients randomized to receive the oral phosphodiesterase-4 inhibitor and 3.9 in 103 patients in the placebo group. Mean visual analog scale (VAS) pain scores were 61.2 and 60.8 in the two groups, respectively.

The primary study endpoint of area under the curve for total number of oral ulcers over a 12-week period (AUCWk0-12) – a measure that reflects the number of oral ulcers that occur over time and also accounts for the recurring-remitting course of oral ulcers – was achieved. AUCWk0-12 was significantly lower in the apremilast group than in the placebo group (129.54 vs. 222.14, respectively; P less than .0001), Gulen Hatemi, MD, reported at the annual meeting of the American College of Rheumatology.

From baseline to week 12, apremilast treatment also resulted in a significantly lower number of oral ulcers (mean of 1.1 vs. 2.0 for placebo at 12 weeks) and significantly reduced pain from oral ulcers at every visit from week 1 through week 12 of the study, compared with placebo (mean VAS score change from baseline, –40.7 vs. –15.9), said Dr. Hatemi, a professor of medicine at Istanbul University.

“The [12-week] complete response rate ... was 53% in the apremilast group and 22.3% in the placebo group. The [12-week] partial response rate ...was 76% in the apremilast group and 48% in the placebo group,” she said, adding that the efficacy of apremilast was sustained with continued treatment through 28 weeks.

Study participants were adults (mean age, 40 years) with active Behçet’s disease and three or more oral ulcers at randomization or two or more at screening and at randomization. All had been previously treated with at least one nonbiologic medication for oral ulcers and were allowed to have received previous biologic therapies for other disease manifestations. Those with active major organ involvement were excluded.

Treatment included a 30-mg dose of apremilast twice daily for 12 weeks or placebo. After 12 weeks, all patients received apremilast through at least 28 weeks of the 64-week study.

At the 28-week analysis, patients who were initially randomized to placebo and who switched to apremilast after week 12 had benefits comparable with those seen in those randomized to apremilast at the start of the study. A complete response was seen in 59% and 62% of patients in the groups, respectively, and a partial response was seen in 90% and 85%, respectively. Additionally, the mean change in the VAS score for oral ulcer pain in the groups at that time was –40.6 and –41.9, Dr. Hatemi said.

Apremilast was well tolerated in this study; the incidence of adverse events was comparable in the treatment and placebo groups during the 12-week placebo-controlled phase of the study – 78.8% and 71.8%, respectively. The most common events were diarrhea, nausea, headache, and upper respiratory tract infection, she said.

“These were generally mild to moderate, and only two patients had to discontinue the study due to gastrointestinal adverse events,” she said, noting that no new safety signals were observed.

Behçet’s disease is a chronic, relapsing, multisystem inflammatory disorder characterized by recurrent oral ulcers that can be disabling and have a substantial effect on quality of life. These findings, which include efficacy data up to 28 weeks and safety data for at least 100 patients exposed to apremilast for at least 1 year, demonstrate the efficacy of apremilast for the treatment oral ulcers in patients with Behçet’s disease, she said, noting that “the safety findings were consistent with the known safety profile of apremilast.”

The RELIEF study was supported by Celgene. Dr. Hatemi reported receiving grant/research support from Celgene and serving as a speaker for AbbVie, Mustafa Nevzet Pharmaceuticals, and UCB.

SOURCE: Hatemi G et al. Arthritis Rheumatol. 2018;70(Suppl 10), Abstract 2789.

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– Apremilast was effective and well tolerated for up to 28 weeks for the treatment of oral ulcers in patients with active Behçet’s disease, based on findings from the randomized, placebo-controlled, phase 3 RELIEF trial.

At baseline, mean oral ulcer counts were 4.2 in 104 patients randomized to receive the oral phosphodiesterase-4 inhibitor and 3.9 in 103 patients in the placebo group. Mean visual analog scale (VAS) pain scores were 61.2 and 60.8 in the two groups, respectively.

The primary study endpoint of area under the curve for total number of oral ulcers over a 12-week period (AUCWk0-12) – a measure that reflects the number of oral ulcers that occur over time and also accounts for the recurring-remitting course of oral ulcers – was achieved. AUCWk0-12 was significantly lower in the apremilast group than in the placebo group (129.54 vs. 222.14, respectively; P less than .0001), Gulen Hatemi, MD, reported at the annual meeting of the American College of Rheumatology.

From baseline to week 12, apremilast treatment also resulted in a significantly lower number of oral ulcers (mean of 1.1 vs. 2.0 for placebo at 12 weeks) and significantly reduced pain from oral ulcers at every visit from week 1 through week 12 of the study, compared with placebo (mean VAS score change from baseline, –40.7 vs. –15.9), said Dr. Hatemi, a professor of medicine at Istanbul University.

“The [12-week] complete response rate ... was 53% in the apremilast group and 22.3% in the placebo group. The [12-week] partial response rate ...was 76% in the apremilast group and 48% in the placebo group,” she said, adding that the efficacy of apremilast was sustained with continued treatment through 28 weeks.

Study participants were adults (mean age, 40 years) with active Behçet’s disease and three or more oral ulcers at randomization or two or more at screening and at randomization. All had been previously treated with at least one nonbiologic medication for oral ulcers and were allowed to have received previous biologic therapies for other disease manifestations. Those with active major organ involvement were excluded.

Treatment included a 30-mg dose of apremilast twice daily for 12 weeks or placebo. After 12 weeks, all patients received apremilast through at least 28 weeks of the 64-week study.

At the 28-week analysis, patients who were initially randomized to placebo and who switched to apremilast after week 12 had benefits comparable with those seen in those randomized to apremilast at the start of the study. A complete response was seen in 59% and 62% of patients in the groups, respectively, and a partial response was seen in 90% and 85%, respectively. Additionally, the mean change in the VAS score for oral ulcer pain in the groups at that time was –40.6 and –41.9, Dr. Hatemi said.

Apremilast was well tolerated in this study; the incidence of adverse events was comparable in the treatment and placebo groups during the 12-week placebo-controlled phase of the study – 78.8% and 71.8%, respectively. The most common events were diarrhea, nausea, headache, and upper respiratory tract infection, she said.

“These were generally mild to moderate, and only two patients had to discontinue the study due to gastrointestinal adverse events,” she said, noting that no new safety signals were observed.

Behçet’s disease is a chronic, relapsing, multisystem inflammatory disorder characterized by recurrent oral ulcers that can be disabling and have a substantial effect on quality of life. These findings, which include efficacy data up to 28 weeks and safety data for at least 100 patients exposed to apremilast for at least 1 year, demonstrate the efficacy of apremilast for the treatment oral ulcers in patients with Behçet’s disease, she said, noting that “the safety findings were consistent with the known safety profile of apremilast.”

The RELIEF study was supported by Celgene. Dr. Hatemi reported receiving grant/research support from Celgene and serving as a speaker for AbbVie, Mustafa Nevzet Pharmaceuticals, and UCB.

SOURCE: Hatemi G et al. Arthritis Rheumatol. 2018;70(Suppl 10), Abstract 2789.

 

– Apremilast was effective and well tolerated for up to 28 weeks for the treatment of oral ulcers in patients with active Behçet’s disease, based on findings from the randomized, placebo-controlled, phase 3 RELIEF trial.

At baseline, mean oral ulcer counts were 4.2 in 104 patients randomized to receive the oral phosphodiesterase-4 inhibitor and 3.9 in 103 patients in the placebo group. Mean visual analog scale (VAS) pain scores were 61.2 and 60.8 in the two groups, respectively.

The primary study endpoint of area under the curve for total number of oral ulcers over a 12-week period (AUCWk0-12) – a measure that reflects the number of oral ulcers that occur over time and also accounts for the recurring-remitting course of oral ulcers – was achieved. AUCWk0-12 was significantly lower in the apremilast group than in the placebo group (129.54 vs. 222.14, respectively; P less than .0001), Gulen Hatemi, MD, reported at the annual meeting of the American College of Rheumatology.

From baseline to week 12, apremilast treatment also resulted in a significantly lower number of oral ulcers (mean of 1.1 vs. 2.0 for placebo at 12 weeks) and significantly reduced pain from oral ulcers at every visit from week 1 through week 12 of the study, compared with placebo (mean VAS score change from baseline, –40.7 vs. –15.9), said Dr. Hatemi, a professor of medicine at Istanbul University.

“The [12-week] complete response rate ... was 53% in the apremilast group and 22.3% in the placebo group. The [12-week] partial response rate ...was 76% in the apremilast group and 48% in the placebo group,” she said, adding that the efficacy of apremilast was sustained with continued treatment through 28 weeks.

Study participants were adults (mean age, 40 years) with active Behçet’s disease and three or more oral ulcers at randomization or two or more at screening and at randomization. All had been previously treated with at least one nonbiologic medication for oral ulcers and were allowed to have received previous biologic therapies for other disease manifestations. Those with active major organ involvement were excluded.

Treatment included a 30-mg dose of apremilast twice daily for 12 weeks or placebo. After 12 weeks, all patients received apremilast through at least 28 weeks of the 64-week study.

At the 28-week analysis, patients who were initially randomized to placebo and who switched to apremilast after week 12 had benefits comparable with those seen in those randomized to apremilast at the start of the study. A complete response was seen in 59% and 62% of patients in the groups, respectively, and a partial response was seen in 90% and 85%, respectively. Additionally, the mean change in the VAS score for oral ulcer pain in the groups at that time was –40.6 and –41.9, Dr. Hatemi said.

Apremilast was well tolerated in this study; the incidence of adverse events was comparable in the treatment and placebo groups during the 12-week placebo-controlled phase of the study – 78.8% and 71.8%, respectively. The most common events were diarrhea, nausea, headache, and upper respiratory tract infection, she said.

“These were generally mild to moderate, and only two patients had to discontinue the study due to gastrointestinal adverse events,” she said, noting that no new safety signals were observed.

Behçet’s disease is a chronic, relapsing, multisystem inflammatory disorder characterized by recurrent oral ulcers that can be disabling and have a substantial effect on quality of life. These findings, which include efficacy data up to 28 weeks and safety data for at least 100 patients exposed to apremilast for at least 1 year, demonstrate the efficacy of apremilast for the treatment oral ulcers in patients with Behçet’s disease, she said, noting that “the safety findings were consistent with the known safety profile of apremilast.”

The RELIEF study was supported by Celgene. Dr. Hatemi reported receiving grant/research support from Celgene and serving as a speaker for AbbVie, Mustafa Nevzet Pharmaceuticals, and UCB.

SOURCE: Hatemi G et al. Arthritis Rheumatol. 2018;70(Suppl 10), Abstract 2789.

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Key clinical point: Apremilast is safe and effective for treating oral ulcers in patients with Behçet’s disease.

Major finding: The AUCWk0-12 was significantly lower with apremilast (129.54) versus placebo (222.14).

Study details: A randomized, placebo-controlled, phase 3 study of 207 patients.

Disclosures: The RELIEF study was supported by Celgene. Dr. Hatemi reported receiving grant/research support from Celgene and serving as a speaker for AbbVie, Mustafa Nevzet Pharmaceuticals, and UCB.

Source: Hatemi G et al. Arthritis Rheumatol. 2018;70(Suppl 10), Abstract 2789

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Depression is linked to seizure frequency in patients with epilepsy

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Depression severity is correlated with seizure frequency and quality of life in adults with epilepsy, according to an analysis presented at the annual meeting of the American Epilepsy Society.

The conclusion comes from a study of 120 people with epilepsy, 62 of whom had at least moderate depression based on the Patient Health Questionnaire-9 (PHQ-9). The Rapid Estimate of Adult Literacy in Medicine (REALM-R), Quality of Life in Epilepsy (QOLIE-10) and Charlson Comorbidity Index were used to assess patients’ health literacy, quality of life, and medical comorbidity, respectively

Among demographic characteristics, only inability to work was significantly associated with depression severity. Higher 30-day seizure frequency, panic disorder, and obsessive-compulsive disorder were correlated with more severe depression severity. Medical comorbidity was not associated with increased risk of depression.

Identifying and treating psychiatric comorbidities should be part of the management of patients with epilepsy, said Martha X. Sajatovic, MD, director of the Neurological and Behavioral Outcomes Center at Case Western Reserve University in Cleveland, who presented the data. “Following up to ensure they receive treatment is vital, because it can truly change patient outcomes and help them achieve their best quality of life.”

The study findings are consistent with those of previous research indicating that people with symptoms of depression are more likely to have more frequent seizures and decreased quality of life, said Dr. Sajatovic.

“Health care providers should screen their epilepsy patients for depression, but they shouldn’t stop there,” she advised. “A person may have depressive symptoms that don’t reach the level of depression but should be assessed for other types of mental health issues that could easily be overlooked.”

Patients with epilepsy should respond to the PHQ-9 annually, or more frequently, if warranted, she added.

“It’s important that people with epilepsy who have depression or other mental health issues get treatment such as cognitive behavioral therapy and medication,” said Dr. Sajatovic. “Even being in a self-management program helps, because the better they are at self management, the less likely they are to suffer negative health effects.”

This study was supported by a grant from the Centers for Disease Control and Prevention SIP 14-007 1U48DP005030.
 

SOURCE: Kumar N et al. AES 2018, Abstract 1.371.

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Depression severity is correlated with seizure frequency and quality of life in adults with epilepsy, according to an analysis presented at the annual meeting of the American Epilepsy Society.

The conclusion comes from a study of 120 people with epilepsy, 62 of whom had at least moderate depression based on the Patient Health Questionnaire-9 (PHQ-9). The Rapid Estimate of Adult Literacy in Medicine (REALM-R), Quality of Life in Epilepsy (QOLIE-10) and Charlson Comorbidity Index were used to assess patients’ health literacy, quality of life, and medical comorbidity, respectively

Among demographic characteristics, only inability to work was significantly associated with depression severity. Higher 30-day seizure frequency, panic disorder, and obsessive-compulsive disorder were correlated with more severe depression severity. Medical comorbidity was not associated with increased risk of depression.

Identifying and treating psychiatric comorbidities should be part of the management of patients with epilepsy, said Martha X. Sajatovic, MD, director of the Neurological and Behavioral Outcomes Center at Case Western Reserve University in Cleveland, who presented the data. “Following up to ensure they receive treatment is vital, because it can truly change patient outcomes and help them achieve their best quality of life.”

The study findings are consistent with those of previous research indicating that people with symptoms of depression are more likely to have more frequent seizures and decreased quality of life, said Dr. Sajatovic.

“Health care providers should screen their epilepsy patients for depression, but they shouldn’t stop there,” she advised. “A person may have depressive symptoms that don’t reach the level of depression but should be assessed for other types of mental health issues that could easily be overlooked.”

Patients with epilepsy should respond to the PHQ-9 annually, or more frequently, if warranted, she added.

“It’s important that people with epilepsy who have depression or other mental health issues get treatment such as cognitive behavioral therapy and medication,” said Dr. Sajatovic. “Even being in a self-management program helps, because the better they are at self management, the less likely they are to suffer negative health effects.”

This study was supported by a grant from the Centers for Disease Control and Prevention SIP 14-007 1U48DP005030.
 

SOURCE: Kumar N et al. AES 2018, Abstract 1.371.

 

Depression severity is correlated with seizure frequency and quality of life in adults with epilepsy, according to an analysis presented at the annual meeting of the American Epilepsy Society.

The conclusion comes from a study of 120 people with epilepsy, 62 of whom had at least moderate depression based on the Patient Health Questionnaire-9 (PHQ-9). The Rapid Estimate of Adult Literacy in Medicine (REALM-R), Quality of Life in Epilepsy (QOLIE-10) and Charlson Comorbidity Index were used to assess patients’ health literacy, quality of life, and medical comorbidity, respectively

Among demographic characteristics, only inability to work was significantly associated with depression severity. Higher 30-day seizure frequency, panic disorder, and obsessive-compulsive disorder were correlated with more severe depression severity. Medical comorbidity was not associated with increased risk of depression.

Identifying and treating psychiatric comorbidities should be part of the management of patients with epilepsy, said Martha X. Sajatovic, MD, director of the Neurological and Behavioral Outcomes Center at Case Western Reserve University in Cleveland, who presented the data. “Following up to ensure they receive treatment is vital, because it can truly change patient outcomes and help them achieve their best quality of life.”

The study findings are consistent with those of previous research indicating that people with symptoms of depression are more likely to have more frequent seizures and decreased quality of life, said Dr. Sajatovic.

“Health care providers should screen their epilepsy patients for depression, but they shouldn’t stop there,” she advised. “A person may have depressive symptoms that don’t reach the level of depression but should be assessed for other types of mental health issues that could easily be overlooked.”

Patients with epilepsy should respond to the PHQ-9 annually, or more frequently, if warranted, she added.

“It’s important that people with epilepsy who have depression or other mental health issues get treatment such as cognitive behavioral therapy and medication,” said Dr. Sajatovic. “Even being in a self-management program helps, because the better they are at self management, the less likely they are to suffer negative health effects.”

This study was supported by a grant from the Centers for Disease Control and Prevention SIP 14-007 1U48DP005030.
 

SOURCE: Kumar N et al. AES 2018, Abstract 1.371.

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Key clinical point: Identification and treatment of psychiatric comorbidities are appropriate components of epilepsy management.

Major finding: Half of participants in a randomized, controlled trial had depression of at least moderate severity.

Study details: Researchers analyzed data from a trial of 120 people with epilepsy.

Disclosures: This study was supported by a grant from the CDC SIP 14-007 1U48DP005030.

Source: Kumar N et al. Abstract 1.371.

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Enzyme-inducing AEDs may raise vitamin D dose requirements

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– Patients taking enzyme-inducing antiepileptic drugs (AEDs) may require a clinically meaningful increase in their vitamin D doses to achieve the same 25-hydroxyvitamin D (25[OH]D) plasma levels as patients taking nonenzyme-inducing AEDs, based on a retrospective chart review presented at the annual meeting of the American Epilepsy Society.

While patients receiving either type of AED had similar average 25(OH)D levels in the study (32.0 ng/mL in the enzyme-inducing AED group and 33.2 ng/mL in the noninducing AED group), those in the enzyme-inducing group required 1,587 U/day to meet the goal – a 409-unit increase in dose, compared with the 1,108 U/day dose taken by patients in the nonenzyme-inducing group.

“Patients taking enzyme-inducing AEDs may benefit from more intensive monitoring of their vitamin D supplementation, and clinicians should anticipate this likely pharmacokinetic interaction,” said Barry E. Gidal, PharmD, professor of pharmacy and neurology at the University of Wisconsin–Madison, and his colleagues.

Researchers have suggested that enzyme-inducing AEDs may affect CYP450 isoenzymes, increase vitamin D metabolism, and reduce 25(OH)D plasma levels. “It follows … that a potential pharmacokinetic interaction could exist between enzyme-inducing AEDs and oral formulations of vitamin D used for supplementation,” the investigators said.

To test the hypothesis, Dr. Gidal and his colleagues reviewed the charts of patients with epilepsy who were on any AED regimen and were prescribed vitamin D at William S. Middleton Memorial Veterans Hospital in Madison, Wisconsin, between January 2013 and September 2017.

The researchers grouped patients by those using enzyme-inducing AEDs and those taking noninducing AEDs. Patients who were taking AEDs in both categories were placed in the enzyme-inducing AED group. Patients with malabsorptive conditions and patients using calcitriol were excluded from the analysis.

Data included AEDs used, prescription and over-the-counter vitamin D use, 25(OH)D plasma concentration, renal function, age, gender, and ethnicity. Patients’ 25(OH)D levels were measured using a chemiluminescence immunoassay, and a minimum 25(OH)D plasma level of 30 ng/mL was the therapeutic goal.

The multivariant analysis was adjusted for potentially confounding variables including 25(OH)D concentration, over-the-counter vitamin D use, chronic kidney disease, age, gender, and ethnicity.

The analysis included 1,113 observations from 315 patients, and 263 of the observations (23.6%) were in the enzyme-inducing AED group. The enzyme-inducing group and noninducing groups were mostly male (90.5% and 91.8%, respectively) and similar in average age (65.9 and 61.4 years, respectively). Variables were evenly distributed between the groups, with the exceptions of chronic kidney disease, which was less common in the enzyme-inducing group (6.1% vs. 13.8%), and ethnicity (78.7% Caucasian in the enzyme-inducing group vs. 87.7% Caucasian in the noninducing group). The most common enzyme-inducing AED was phenytoin (50.6%), followed by carbamazepine (31.9%), phenobarbital (14.1%), oxcarbazepine (6.8%), primidone (1.9%), and eslicarbazepine (0.8%).

Dr. Gidal reported honoraria from Eisai, Sunovion, Lundbeck, and GW Pharmaceuticals.
 

SOURCE: Gidal BE et al. AES 2018, Abstract 1.315.

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– Patients taking enzyme-inducing antiepileptic drugs (AEDs) may require a clinically meaningful increase in their vitamin D doses to achieve the same 25-hydroxyvitamin D (25[OH]D) plasma levels as patients taking nonenzyme-inducing AEDs, based on a retrospective chart review presented at the annual meeting of the American Epilepsy Society.

While patients receiving either type of AED had similar average 25(OH)D levels in the study (32.0 ng/mL in the enzyme-inducing AED group and 33.2 ng/mL in the noninducing AED group), those in the enzyme-inducing group required 1,587 U/day to meet the goal – a 409-unit increase in dose, compared with the 1,108 U/day dose taken by patients in the nonenzyme-inducing group.

“Patients taking enzyme-inducing AEDs may benefit from more intensive monitoring of their vitamin D supplementation, and clinicians should anticipate this likely pharmacokinetic interaction,” said Barry E. Gidal, PharmD, professor of pharmacy and neurology at the University of Wisconsin–Madison, and his colleagues.

Researchers have suggested that enzyme-inducing AEDs may affect CYP450 isoenzymes, increase vitamin D metabolism, and reduce 25(OH)D plasma levels. “It follows … that a potential pharmacokinetic interaction could exist between enzyme-inducing AEDs and oral formulations of vitamin D used for supplementation,” the investigators said.

To test the hypothesis, Dr. Gidal and his colleagues reviewed the charts of patients with epilepsy who were on any AED regimen and were prescribed vitamin D at William S. Middleton Memorial Veterans Hospital in Madison, Wisconsin, between January 2013 and September 2017.

The researchers grouped patients by those using enzyme-inducing AEDs and those taking noninducing AEDs. Patients who were taking AEDs in both categories were placed in the enzyme-inducing AED group. Patients with malabsorptive conditions and patients using calcitriol were excluded from the analysis.

Data included AEDs used, prescription and over-the-counter vitamin D use, 25(OH)D plasma concentration, renal function, age, gender, and ethnicity. Patients’ 25(OH)D levels were measured using a chemiluminescence immunoassay, and a minimum 25(OH)D plasma level of 30 ng/mL was the therapeutic goal.

The multivariant analysis was adjusted for potentially confounding variables including 25(OH)D concentration, over-the-counter vitamin D use, chronic kidney disease, age, gender, and ethnicity.

The analysis included 1,113 observations from 315 patients, and 263 of the observations (23.6%) were in the enzyme-inducing AED group. The enzyme-inducing group and noninducing groups were mostly male (90.5% and 91.8%, respectively) and similar in average age (65.9 and 61.4 years, respectively). Variables were evenly distributed between the groups, with the exceptions of chronic kidney disease, which was less common in the enzyme-inducing group (6.1% vs. 13.8%), and ethnicity (78.7% Caucasian in the enzyme-inducing group vs. 87.7% Caucasian in the noninducing group). The most common enzyme-inducing AED was phenytoin (50.6%), followed by carbamazepine (31.9%), phenobarbital (14.1%), oxcarbazepine (6.8%), primidone (1.9%), and eslicarbazepine (0.8%).

Dr. Gidal reported honoraria from Eisai, Sunovion, Lundbeck, and GW Pharmaceuticals.
 

SOURCE: Gidal BE et al. AES 2018, Abstract 1.315.

 

– Patients taking enzyme-inducing antiepileptic drugs (AEDs) may require a clinically meaningful increase in their vitamin D doses to achieve the same 25-hydroxyvitamin D (25[OH]D) plasma levels as patients taking nonenzyme-inducing AEDs, based on a retrospective chart review presented at the annual meeting of the American Epilepsy Society.

While patients receiving either type of AED had similar average 25(OH)D levels in the study (32.0 ng/mL in the enzyme-inducing AED group and 33.2 ng/mL in the noninducing AED group), those in the enzyme-inducing group required 1,587 U/day to meet the goal – a 409-unit increase in dose, compared with the 1,108 U/day dose taken by patients in the nonenzyme-inducing group.

“Patients taking enzyme-inducing AEDs may benefit from more intensive monitoring of their vitamin D supplementation, and clinicians should anticipate this likely pharmacokinetic interaction,” said Barry E. Gidal, PharmD, professor of pharmacy and neurology at the University of Wisconsin–Madison, and his colleagues.

Researchers have suggested that enzyme-inducing AEDs may affect CYP450 isoenzymes, increase vitamin D metabolism, and reduce 25(OH)D plasma levels. “It follows … that a potential pharmacokinetic interaction could exist between enzyme-inducing AEDs and oral formulations of vitamin D used for supplementation,” the investigators said.

To test the hypothesis, Dr. Gidal and his colleagues reviewed the charts of patients with epilepsy who were on any AED regimen and were prescribed vitamin D at William S. Middleton Memorial Veterans Hospital in Madison, Wisconsin, between January 2013 and September 2017.

The researchers grouped patients by those using enzyme-inducing AEDs and those taking noninducing AEDs. Patients who were taking AEDs in both categories were placed in the enzyme-inducing AED group. Patients with malabsorptive conditions and patients using calcitriol were excluded from the analysis.

Data included AEDs used, prescription and over-the-counter vitamin D use, 25(OH)D plasma concentration, renal function, age, gender, and ethnicity. Patients’ 25(OH)D levels were measured using a chemiluminescence immunoassay, and a minimum 25(OH)D plasma level of 30 ng/mL was the therapeutic goal.

The multivariant analysis was adjusted for potentially confounding variables including 25(OH)D concentration, over-the-counter vitamin D use, chronic kidney disease, age, gender, and ethnicity.

The analysis included 1,113 observations from 315 patients, and 263 of the observations (23.6%) were in the enzyme-inducing AED group. The enzyme-inducing group and noninducing groups were mostly male (90.5% and 91.8%, respectively) and similar in average age (65.9 and 61.4 years, respectively). Variables were evenly distributed between the groups, with the exceptions of chronic kidney disease, which was less common in the enzyme-inducing group (6.1% vs. 13.8%), and ethnicity (78.7% Caucasian in the enzyme-inducing group vs. 87.7% Caucasian in the noninducing group). The most common enzyme-inducing AED was phenytoin (50.6%), followed by carbamazepine (31.9%), phenobarbital (14.1%), oxcarbazepine (6.8%), primidone (1.9%), and eslicarbazepine (0.8%).

Dr. Gidal reported honoraria from Eisai, Sunovion, Lundbeck, and GW Pharmaceuticals.
 

SOURCE: Gidal BE et al. AES 2018, Abstract 1.315.

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Key clinical point: Enzyme-inducing antiepileptic drugs affect vitamin D dose requirements.

Major finding: Patients taking enzyme-inducing antiepileptic drugs require a higher daily dose of vitamin D, compared with patients taking noninducing antiepileptic drugs (1,587 U/day vs. 1,108 U/day).

Study details: A retrospective chart review of data from 315 patients treated at a Veterans Affairs hospital.

Disclosures: Dr. Gidal reported honoraria from Eisai, Sunovion, Lundbeck, and GW Pharmaceuticals..

Source: Gidal BE et al. AES 2018, Abstract 1.315.

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Teenagers with epilepsy may benefit from depression screening

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Fri, 01/18/2019 - 18:09

Clinicians should screen patients with pediatric epilepsy for depression regularly, according to research described at the annual meeting of the American Epilepsy Society. Referral to a mental health provider is adequate for most patients with moderately severe symptoms of depression, but some patients may require active intervention during the clinical visit, said the researchers.

Dr. Susan Arnold

“We know that depression is more common in people with epilepsy, compared to the general population, but there is less information about depression in children and teens than adults, and little is known about the factors that increase the likelihood of depressive symptoms,” said Hillary Thomas, PhD, a pediatric psychologist at Children’s Medical Center in Dallas. “Depression screening should be routine at epilepsy treatment centers and can identify children and teens who would benefit from intervention.”

Following 2015 guidelines from the American Academy of Neurology, the Comprehensive Epilepsy Center at Children’s Health System in Dallas developed a behavioral health screening protocol for teens with epilepsy. The center aims to identify patients with depressive symptoms and ensure that they are referred to appropriate behavioral health practitioners. Clinicians also review the screening data and seizure variables for their potential implications for clinical care. Researchers at the center also seek to elucidate the relationship between depressive symptoms and seizure diagnosis and treatment.

As part of the protocol, Dr. Thomas and her colleagues administer the Patient Health Questionnaire-9 (adolescent version) to all patients aged 15-18 years during their visit to the epilepsy clinic. Patients with intellectual disability or other factors that prevent them from providing valid responses are excluded. If a patient’s PHQ-9 score indicates at least moderately severe depressive symptoms, or if he or she reports suicidal ideation, clinicians follow a specific response protocol that includes providing referrals, encouraging follow-up with the patient’s current mental health provider, and obtaining a suicide risk assessment from a psychologist or social worker. After the screener is completed, clinicians retrieve demographic and clinical data (e.g., seizure diagnosis, medication, number of clinic or emergency department visits) from the patient’s medical record and include them in a database for subsequent analysis.

Dr. Thomas and her colleagues presented data from 394 youth with epilepsy whom they had screened. Patients’ mean age was 16 years, and half of the population was female. The study population had rates of depression similar to those identified in previous studies, said Dr. Thomas. Approximately 87% of patients had minimal or mild depressive symptoms, and 8% had moderately severe depressive symptoms. Furthermore, 5% of the patients reported suicidal ideation or previous suicide attempt. Several of the patients with suicidal ideation had a current mental health provider, and the others required an in-clinic risk assessment. Overall, 13% of the population required behavioral health referral or intervention. When the researchers conducted chi-squared analysis, they found no significant association between seizure type and depression severity.

“Our results don’t mean that only 13% of the teens with epilepsy had depressive symptoms,” said Susan Arnold, MD, director of the Comprehensive Epilepsy Center and a coauthor of the study. “They indicate the significant percentage of teens whose level of depressive symptoms warranted behavioral health referrals or further evaluation or even intervention during a clinic visit. Health care providers need to be vigilant about continually screening children and teens for depression.” As part of each patient’s comprehensive care, epilepsy treatment centers should provide psychosocial teams that include social workers or psychologists, she added.

The investigators plan to continue analyzing the data for specific depression symptoms that are most common in teens. These symptoms could be the basis for developing additional resources for families, such as lists of warning signs and guides to symptom management, as well as group therapy and support groups.
 

[email protected]

SOURCE: Thomas HM et al. Abstract 1.388.

 

 

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Clinicians should screen patients with pediatric epilepsy for depression regularly, according to research described at the annual meeting of the American Epilepsy Society. Referral to a mental health provider is adequate for most patients with moderately severe symptoms of depression, but some patients may require active intervention during the clinical visit, said the researchers.

Dr. Susan Arnold

“We know that depression is more common in people with epilepsy, compared to the general population, but there is less information about depression in children and teens than adults, and little is known about the factors that increase the likelihood of depressive symptoms,” said Hillary Thomas, PhD, a pediatric psychologist at Children’s Medical Center in Dallas. “Depression screening should be routine at epilepsy treatment centers and can identify children and teens who would benefit from intervention.”

Following 2015 guidelines from the American Academy of Neurology, the Comprehensive Epilepsy Center at Children’s Health System in Dallas developed a behavioral health screening protocol for teens with epilepsy. The center aims to identify patients with depressive symptoms and ensure that they are referred to appropriate behavioral health practitioners. Clinicians also review the screening data and seizure variables for their potential implications for clinical care. Researchers at the center also seek to elucidate the relationship between depressive symptoms and seizure diagnosis and treatment.

As part of the protocol, Dr. Thomas and her colleagues administer the Patient Health Questionnaire-9 (adolescent version) to all patients aged 15-18 years during their visit to the epilepsy clinic. Patients with intellectual disability or other factors that prevent them from providing valid responses are excluded. If a patient’s PHQ-9 score indicates at least moderately severe depressive symptoms, or if he or she reports suicidal ideation, clinicians follow a specific response protocol that includes providing referrals, encouraging follow-up with the patient’s current mental health provider, and obtaining a suicide risk assessment from a psychologist or social worker. After the screener is completed, clinicians retrieve demographic and clinical data (e.g., seizure diagnosis, medication, number of clinic or emergency department visits) from the patient’s medical record and include them in a database for subsequent analysis.

Dr. Thomas and her colleagues presented data from 394 youth with epilepsy whom they had screened. Patients’ mean age was 16 years, and half of the population was female. The study population had rates of depression similar to those identified in previous studies, said Dr. Thomas. Approximately 87% of patients had minimal or mild depressive symptoms, and 8% had moderately severe depressive symptoms. Furthermore, 5% of the patients reported suicidal ideation or previous suicide attempt. Several of the patients with suicidal ideation had a current mental health provider, and the others required an in-clinic risk assessment. Overall, 13% of the population required behavioral health referral or intervention. When the researchers conducted chi-squared analysis, they found no significant association between seizure type and depression severity.

“Our results don’t mean that only 13% of the teens with epilepsy had depressive symptoms,” said Susan Arnold, MD, director of the Comprehensive Epilepsy Center and a coauthor of the study. “They indicate the significant percentage of teens whose level of depressive symptoms warranted behavioral health referrals or further evaluation or even intervention during a clinic visit. Health care providers need to be vigilant about continually screening children and teens for depression.” As part of each patient’s comprehensive care, epilepsy treatment centers should provide psychosocial teams that include social workers or psychologists, she added.

The investigators plan to continue analyzing the data for specific depression symptoms that are most common in teens. These symptoms could be the basis for developing additional resources for families, such as lists of warning signs and guides to symptom management, as well as group therapy and support groups.
 

[email protected]

SOURCE: Thomas HM et al. Abstract 1.388.

 

 

Clinicians should screen patients with pediatric epilepsy for depression regularly, according to research described at the annual meeting of the American Epilepsy Society. Referral to a mental health provider is adequate for most patients with moderately severe symptoms of depression, but some patients may require active intervention during the clinical visit, said the researchers.

Dr. Susan Arnold

“We know that depression is more common in people with epilepsy, compared to the general population, but there is less information about depression in children and teens than adults, and little is known about the factors that increase the likelihood of depressive symptoms,” said Hillary Thomas, PhD, a pediatric psychologist at Children’s Medical Center in Dallas. “Depression screening should be routine at epilepsy treatment centers and can identify children and teens who would benefit from intervention.”

Following 2015 guidelines from the American Academy of Neurology, the Comprehensive Epilepsy Center at Children’s Health System in Dallas developed a behavioral health screening protocol for teens with epilepsy. The center aims to identify patients with depressive symptoms and ensure that they are referred to appropriate behavioral health practitioners. Clinicians also review the screening data and seizure variables for their potential implications for clinical care. Researchers at the center also seek to elucidate the relationship between depressive symptoms and seizure diagnosis and treatment.

As part of the protocol, Dr. Thomas and her colleagues administer the Patient Health Questionnaire-9 (adolescent version) to all patients aged 15-18 years during their visit to the epilepsy clinic. Patients with intellectual disability or other factors that prevent them from providing valid responses are excluded. If a patient’s PHQ-9 score indicates at least moderately severe depressive symptoms, or if he or she reports suicidal ideation, clinicians follow a specific response protocol that includes providing referrals, encouraging follow-up with the patient’s current mental health provider, and obtaining a suicide risk assessment from a psychologist or social worker. After the screener is completed, clinicians retrieve demographic and clinical data (e.g., seizure diagnosis, medication, number of clinic or emergency department visits) from the patient’s medical record and include them in a database for subsequent analysis.

Dr. Thomas and her colleagues presented data from 394 youth with epilepsy whom they had screened. Patients’ mean age was 16 years, and half of the population was female. The study population had rates of depression similar to those identified in previous studies, said Dr. Thomas. Approximately 87% of patients had minimal or mild depressive symptoms, and 8% had moderately severe depressive symptoms. Furthermore, 5% of the patients reported suicidal ideation or previous suicide attempt. Several of the patients with suicidal ideation had a current mental health provider, and the others required an in-clinic risk assessment. Overall, 13% of the population required behavioral health referral or intervention. When the researchers conducted chi-squared analysis, they found no significant association between seizure type and depression severity.

“Our results don’t mean that only 13% of the teens with epilepsy had depressive symptoms,” said Susan Arnold, MD, director of the Comprehensive Epilepsy Center and a coauthor of the study. “They indicate the significant percentage of teens whose level of depressive symptoms warranted behavioral health referrals or further evaluation or even intervention during a clinic visit. Health care providers need to be vigilant about continually screening children and teens for depression.” As part of each patient’s comprehensive care, epilepsy treatment centers should provide psychosocial teams that include social workers or psychologists, she added.

The investigators plan to continue analyzing the data for specific depression symptoms that are most common in teens. These symptoms could be the basis for developing additional resources for families, such as lists of warning signs and guides to symptom management, as well as group therapy and support groups.
 

[email protected]

SOURCE: Thomas HM et al. Abstract 1.388.

 

 

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Key clinical point: Screening children with epilepsy regularly for depression may be advisable.

Major finding: About 13% of patients screened required referral or intervention.

Study details: Prospective study of 394 patients with epilepsy.

Disclosures: The investigators have no disclosures and received no funding for this study.

Source: Thomas HM et al. Abstract 1.388.

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Gatekeeper

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One evening as the oncology fellow on call, I received a phone call from the ICU fellow.

“Can you meet me in the emergency room?” he asked. “I want to make sure we’re on the same page.”

A patient we had discharged from the hospital 2 days before was back. He had metastatic stomach cancer that had spread into his lungs and the lymph nodes in his chest. While he was in the hospital, he had required several liters of oxygen to maintain a normal work of breathing.

But now, he was in the emergency room, he was requiring a full face mask to help him breathe – and his oxygen levels were still dropping.

The ICU had been called. The next step along the algorithm of worsening breathing would be intubation. They would have to sedate him, put a breathing tube down his throat, and connect him to a ventilator to keep him alive.

But they didn’t want to do that if he was dying from his cancer.

Hence the call to me. My job, as the oncologist on call, was to answer the question: Is he dying?

Specifically, that meant weigh in on his cancer prognosis. Put his disease into context. Does he have any more options, chemotherapy or otherwise?

As an oncology fellow, I’ve found this to be one of the most common calls I get. Someone is critically ill and they need something to survive – maybe it’s intubation; maybe it’s surgery. The patient also happens to have metastatic cancer. The question posed to me is: Should we proceed?

Dr. Ilana Yurkiewicz

It’s also one of the most difficult calls. Because doctors are historically bad at prognosticating. Because often I’m meeting the patient for the first time. Because the decision is huge and often final, and because both options are bad.

Suppose I say he has a good year or 2 ahead of him, and we intubate him – and then he never comes off the ventilator. We are eventually forced to withdraw care, and to the family it’s as though they are killing their father. It’s traumatic; it’s painful; and it deprives someone of a comfortable passing. Suppose I say he is dying from his cancer and we decide against a breathing tube. If I am wrong in that direction, a person’s life is cut short. It’s a perfect storm of high risk and low certainty.

Many people with metastatic cancer say they wouldn’t want invasive treatment near the end of life. But how do we know when it’s the end? There is still a moment when you must determine: Is this it? The truth is it’s not always clear.

 

 

Whenever I can, I reach out to the primary oncologist who knows the patient best. Then, I do a quick search for something reversible. Did the patient take too much morphine at home, and should we trial a dose of Narcan? Does he have a pneumonia that could be cured with antibiotics, a blood clot that could improve with blood thinners, or some extra fluid that can be diuresed? But usually it’s a mix, and even if there is a reversible injury, it can tip the very ill person over to the irreversible. This is how passing away from an aggressive cancer plays out.

Down in the emergency room, my patient’s breathing is rapid. His chest is heaving. The nurse shows me his blood gas with a carbon dioxide level more than twice the upper limit of normal. Now fading in and out of consciousness, he is a different man from the one who had walked out of the hospital 2 days earlier.

His daughter stands next to him. “He always said he wanted to do everything. I think we should give the breathing tube a try,” she says.

I tell her my concerns. I am afraid if we do it the likelihood of ever coming off is slim. And if we place a breathing tube he would have to be sedated so as not to be uncomfortable, and you won’t be able to communicate with him. You can’t say good bye, or I love you. If we keep the mask, he may wake up enough to interact.

The daughter – whom I knew well from prior visits, who was always articulate and poised and the spokesperson for the family – had held it together this entire time. Now, she breaks down. We all wait as I hand her a box of tissues. I look down, channeling all of my energy into not crying in front of her.

He’s waking up, one of us notes.

She goes over. “I need to ask him,” she says.

“Papa.”

At first he doesn’t answer.

“Papa, do you want the breathing tube?”

“No,” he says.

“Without it you can die. You know that, Papa?”

“No breathing tube,” he says.

“OK,” she turns to us, with tears of sadness but also what seems like relief.

Forty-eight hours later, he passed away. His family had time to come in, and he had periods of alertness where he could speak with them. They were able to say good-bye. He was able to say I love you.

Another patient’s wife once told me he had given her the “gift of clarity” when he plainly stated before he passed that he didn’t want to be saved. She didn’t have to make the decision for him, and neither did the doctors. I liked that term, and I thought about it then.

I am grateful my patient’s wishes were clear. But we aren’t always so lucky. It’s a chilling part of the job description, being a gatekeeper to the question: Is this the end?

Dr. Yurkiewicz is a fellow in hematology and oncology at Stanford (Calif.) University. Follow her on Twitter @ilanayurkiewicz.

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One evening as the oncology fellow on call, I received a phone call from the ICU fellow.

“Can you meet me in the emergency room?” he asked. “I want to make sure we’re on the same page.”

A patient we had discharged from the hospital 2 days before was back. He had metastatic stomach cancer that had spread into his lungs and the lymph nodes in his chest. While he was in the hospital, he had required several liters of oxygen to maintain a normal work of breathing.

But now, he was in the emergency room, he was requiring a full face mask to help him breathe – and his oxygen levels were still dropping.

The ICU had been called. The next step along the algorithm of worsening breathing would be intubation. They would have to sedate him, put a breathing tube down his throat, and connect him to a ventilator to keep him alive.

But they didn’t want to do that if he was dying from his cancer.

Hence the call to me. My job, as the oncologist on call, was to answer the question: Is he dying?

Specifically, that meant weigh in on his cancer prognosis. Put his disease into context. Does he have any more options, chemotherapy or otherwise?

As an oncology fellow, I’ve found this to be one of the most common calls I get. Someone is critically ill and they need something to survive – maybe it’s intubation; maybe it’s surgery. The patient also happens to have metastatic cancer. The question posed to me is: Should we proceed?

Dr. Ilana Yurkiewicz

It’s also one of the most difficult calls. Because doctors are historically bad at prognosticating. Because often I’m meeting the patient for the first time. Because the decision is huge and often final, and because both options are bad.

Suppose I say he has a good year or 2 ahead of him, and we intubate him – and then he never comes off the ventilator. We are eventually forced to withdraw care, and to the family it’s as though they are killing their father. It’s traumatic; it’s painful; and it deprives someone of a comfortable passing. Suppose I say he is dying from his cancer and we decide against a breathing tube. If I am wrong in that direction, a person’s life is cut short. It’s a perfect storm of high risk and low certainty.

Many people with metastatic cancer say they wouldn’t want invasive treatment near the end of life. But how do we know when it’s the end? There is still a moment when you must determine: Is this it? The truth is it’s not always clear.

 

 

Whenever I can, I reach out to the primary oncologist who knows the patient best. Then, I do a quick search for something reversible. Did the patient take too much morphine at home, and should we trial a dose of Narcan? Does he have a pneumonia that could be cured with antibiotics, a blood clot that could improve with blood thinners, or some extra fluid that can be diuresed? But usually it’s a mix, and even if there is a reversible injury, it can tip the very ill person over to the irreversible. This is how passing away from an aggressive cancer plays out.

Down in the emergency room, my patient’s breathing is rapid. His chest is heaving. The nurse shows me his blood gas with a carbon dioxide level more than twice the upper limit of normal. Now fading in and out of consciousness, he is a different man from the one who had walked out of the hospital 2 days earlier.

His daughter stands next to him. “He always said he wanted to do everything. I think we should give the breathing tube a try,” she says.

I tell her my concerns. I am afraid if we do it the likelihood of ever coming off is slim. And if we place a breathing tube he would have to be sedated so as not to be uncomfortable, and you won’t be able to communicate with him. You can’t say good bye, or I love you. If we keep the mask, he may wake up enough to interact.

The daughter – whom I knew well from prior visits, who was always articulate and poised and the spokesperson for the family – had held it together this entire time. Now, she breaks down. We all wait as I hand her a box of tissues. I look down, channeling all of my energy into not crying in front of her.

He’s waking up, one of us notes.

She goes over. “I need to ask him,” she says.

“Papa.”

At first he doesn’t answer.

“Papa, do you want the breathing tube?”

“No,” he says.

“Without it you can die. You know that, Papa?”

“No breathing tube,” he says.

“OK,” she turns to us, with tears of sadness but also what seems like relief.

Forty-eight hours later, he passed away. His family had time to come in, and he had periods of alertness where he could speak with them. They were able to say good-bye. He was able to say I love you.

Another patient’s wife once told me he had given her the “gift of clarity” when he plainly stated before he passed that he didn’t want to be saved. She didn’t have to make the decision for him, and neither did the doctors. I liked that term, and I thought about it then.

I am grateful my patient’s wishes were clear. But we aren’t always so lucky. It’s a chilling part of the job description, being a gatekeeper to the question: Is this the end?

Dr. Yurkiewicz is a fellow in hematology and oncology at Stanford (Calif.) University. Follow her on Twitter @ilanayurkiewicz.


One evening as the oncology fellow on call, I received a phone call from the ICU fellow.

“Can you meet me in the emergency room?” he asked. “I want to make sure we’re on the same page.”

A patient we had discharged from the hospital 2 days before was back. He had metastatic stomach cancer that had spread into his lungs and the lymph nodes in his chest. While he was in the hospital, he had required several liters of oxygen to maintain a normal work of breathing.

But now, he was in the emergency room, he was requiring a full face mask to help him breathe – and his oxygen levels were still dropping.

The ICU had been called. The next step along the algorithm of worsening breathing would be intubation. They would have to sedate him, put a breathing tube down his throat, and connect him to a ventilator to keep him alive.

But they didn’t want to do that if he was dying from his cancer.

Hence the call to me. My job, as the oncologist on call, was to answer the question: Is he dying?

Specifically, that meant weigh in on his cancer prognosis. Put his disease into context. Does he have any more options, chemotherapy or otherwise?

As an oncology fellow, I’ve found this to be one of the most common calls I get. Someone is critically ill and they need something to survive – maybe it’s intubation; maybe it’s surgery. The patient also happens to have metastatic cancer. The question posed to me is: Should we proceed?

Dr. Ilana Yurkiewicz

It’s also one of the most difficult calls. Because doctors are historically bad at prognosticating. Because often I’m meeting the patient for the first time. Because the decision is huge and often final, and because both options are bad.

Suppose I say he has a good year or 2 ahead of him, and we intubate him – and then he never comes off the ventilator. We are eventually forced to withdraw care, and to the family it’s as though they are killing their father. It’s traumatic; it’s painful; and it deprives someone of a comfortable passing. Suppose I say he is dying from his cancer and we decide against a breathing tube. If I am wrong in that direction, a person’s life is cut short. It’s a perfect storm of high risk and low certainty.

Many people with metastatic cancer say they wouldn’t want invasive treatment near the end of life. But how do we know when it’s the end? There is still a moment when you must determine: Is this it? The truth is it’s not always clear.

 

 

Whenever I can, I reach out to the primary oncologist who knows the patient best. Then, I do a quick search for something reversible. Did the patient take too much morphine at home, and should we trial a dose of Narcan? Does he have a pneumonia that could be cured with antibiotics, a blood clot that could improve with blood thinners, or some extra fluid that can be diuresed? But usually it’s a mix, and even if there is a reversible injury, it can tip the very ill person over to the irreversible. This is how passing away from an aggressive cancer plays out.

Down in the emergency room, my patient’s breathing is rapid. His chest is heaving. The nurse shows me his blood gas with a carbon dioxide level more than twice the upper limit of normal. Now fading in and out of consciousness, he is a different man from the one who had walked out of the hospital 2 days earlier.

His daughter stands next to him. “He always said he wanted to do everything. I think we should give the breathing tube a try,” she says.

I tell her my concerns. I am afraid if we do it the likelihood of ever coming off is slim. And if we place a breathing tube he would have to be sedated so as not to be uncomfortable, and you won’t be able to communicate with him. You can’t say good bye, or I love you. If we keep the mask, he may wake up enough to interact.

The daughter – whom I knew well from prior visits, who was always articulate and poised and the spokesperson for the family – had held it together this entire time. Now, she breaks down. We all wait as I hand her a box of tissues. I look down, channeling all of my energy into not crying in front of her.

He’s waking up, one of us notes.

She goes over. “I need to ask him,” she says.

“Papa.”

At first he doesn’t answer.

“Papa, do you want the breathing tube?”

“No,” he says.

“Without it you can die. You know that, Papa?”

“No breathing tube,” he says.

“OK,” she turns to us, with tears of sadness but also what seems like relief.

Forty-eight hours later, he passed away. His family had time to come in, and he had periods of alertness where he could speak with them. They were able to say good-bye. He was able to say I love you.

Another patient’s wife once told me he had given her the “gift of clarity” when he plainly stated before he passed that he didn’t want to be saved. She didn’t have to make the decision for him, and neither did the doctors. I liked that term, and I thought about it then.

I am grateful my patient’s wishes were clear. But we aren’t always so lucky. It’s a chilling part of the job description, being a gatekeeper to the question: Is this the end?

Dr. Yurkiewicz is a fellow in hematology and oncology at Stanford (Calif.) University. Follow her on Twitter @ilanayurkiewicz.

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After seven years at the helm of the Journal of Hospital Medicine, I am both pleased to hand over the reins and sad to let them go. My time as Editor in Chief has been wonderful, challenging, and fulfilling.

When I began my tenure, JHM managed approximately 350 papers annually, and published 10 times per year. We had no social media presence, a developing editorial sense (and developing Editor in Chief), and a pool of hard-working and passionate Editors. As of this year, we have handled more than 700 papers and are publishing content monthly, online only, and online first. Our dedicated team is deeply passionate about making every paper better through interaction with the authors—whether we accept it for publication or not.

JHM has added a presence on Facebook and Twitter, launched a Twitter Journal Club as a regular offering (#JHMChat), added visual abstracts to our Tweets and Facebook postings, and researched how these novel approaches increase not only the Journal’s social media presence but also its public face. Our efforts in social media were trendsetting in peer-reviewed literature, and the Editors who lead those efforts—Vineet Arora and Charlie Wray—are asked to consult for other journals regularly.

We launched two new series— Choosing Wisely®: Next Steps, and Choosing Wisely®: Things We Do For No Reason—with help from the ABIM Foundation and visionary Editors, Andy Masica, Ann Sheehy, and Lenny Feldman. These papers have pushed Hospitalists and Hospital Medicine to think carefully about the simple things we do every day, to think broadly about how to move past the initial ‘low-hanging fruit’ of value improvement, and point us towards policy and intervention approaches that are disruptive rather than incremental.

A special thank you to Som Mookherjee, Brian Harte, Dan Hunt, and Read Pierce who ably developed the Clinical Care Conundrums and Review series. They are assisted by teams of national correspondents and many contributors who’ve submitted work for those series.

I have been blessed by a team of more than a dozen Associate Editors who have ably, expeditiously, and collegially managed more than 2,000 papers. These Editors work out of a sense of altruism and commitment to Hospital Medicine and have made huge individual contributions to JHM through their reviewing expertise and ensuring that the editorial sense for JHM is as broad and innovative as our field.

Finally, I must thank my core team of Senior Deputy Editors who have shouldered the majority of editorial work, mentored Editors (including me) and Peer Reviewers, and provided strategic guidance.

How peer-reviewed journals are published is changing rapidly. Setting aside the questions of how we consume our medical literature and the transition from paper to digital, old financial models depending on subscriptions and advertising are either dying or evolving into something very different. The challenge is that the new model is very unclear and the old model based on ads and subscriptions is clearly nonviable but is the primary way to support the work of producing a journal. Moving from the current model to one based on clicks, views, or downloads will come down to who will derive benefit from those clicks/downloads, who will be willing to pay to read and learn from the work of authors, or who views that activity as being worthy enough advertise somewhere in that process or to monetize the data garnered from readers’ activities. In addition, many journals, including JHM, are supported by professional societies. While professional societies have a goal to serve their members, the goal of the peer-reviewed journal is to independently and broadly represent the field. One must reflect the other, but space between the two will always be required.

The speed with which research takes place is too slow, and the process of getting evidence into print (much less adopted) is even slower. But, this too is changing; the role of peer review and the publication process is evolving. In order to speed the potential discovery of new innovations, prepublication repositories (such as BioRxViv) are gaining popularity; well-publicized scandals around peer reviewing rings 1 have not gone unnoticed, and have produced greater interest in using prepublication comments and online discussions as early forms of review. As a result, the disintermediation between scientist and ‘evidence’ is paralleling the disintermediation between events and messengers elsewhere. One need only review Twitter for a moment to get a sense for how crowdsourcing can lead to evidence (or news) generation for good or ill. I agree that while the end of journals (as we understand them now) is upon us, these are also opportunities for JHM as it enters its new phase and a place for leadership. 2

I am proud of what we have done at JHM in the last seven years. We have grown substantially. We have innovated and provided great service to our authors and the field of Hospital Medicine. Our growth and forward-looking approaches to social media and our digital footprint put the journal on a great path towards adapting to the trends in Hospital Medicine research and peer-reviewed publishing. Our focus on being doctors who care for patients and our teams—not just doctors who care for hospitals—is supporting the field and our practice. I look forward to seeing where JHM goes next.

 

 

 

References

1. Retraction Watch. BioMedCentral retracting 43 papers for fake peer reviews. March 26, 2015; http://retractionwatch.com/2015/03/26/biomed-central-retracting-43-papers-for-fake-peer-review/. Accessed November 12, 2018.
2. Krumholz HM. The End of Journals. Circ Cardiovasc Qual Outcomes. 2015;8(6):533-534. doi: 10.1161/CIRCOUTCOMES.115.002415. PubMed

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After seven years at the helm of the Journal of Hospital Medicine, I am both pleased to hand over the reins and sad to let them go. My time as Editor in Chief has been wonderful, challenging, and fulfilling.

When I began my tenure, JHM managed approximately 350 papers annually, and published 10 times per year. We had no social media presence, a developing editorial sense (and developing Editor in Chief), and a pool of hard-working and passionate Editors. As of this year, we have handled more than 700 papers and are publishing content monthly, online only, and online first. Our dedicated team is deeply passionate about making every paper better through interaction with the authors—whether we accept it for publication or not.

JHM has added a presence on Facebook and Twitter, launched a Twitter Journal Club as a regular offering (#JHMChat), added visual abstracts to our Tweets and Facebook postings, and researched how these novel approaches increase not only the Journal’s social media presence but also its public face. Our efforts in social media were trendsetting in peer-reviewed literature, and the Editors who lead those efforts—Vineet Arora and Charlie Wray—are asked to consult for other journals regularly.

We launched two new series— Choosing Wisely®: Next Steps, and Choosing Wisely®: Things We Do For No Reason—with help from the ABIM Foundation and visionary Editors, Andy Masica, Ann Sheehy, and Lenny Feldman. These papers have pushed Hospitalists and Hospital Medicine to think carefully about the simple things we do every day, to think broadly about how to move past the initial ‘low-hanging fruit’ of value improvement, and point us towards policy and intervention approaches that are disruptive rather than incremental.

A special thank you to Som Mookherjee, Brian Harte, Dan Hunt, and Read Pierce who ably developed the Clinical Care Conundrums and Review series. They are assisted by teams of national correspondents and many contributors who’ve submitted work for those series.

I have been blessed by a team of more than a dozen Associate Editors who have ably, expeditiously, and collegially managed more than 2,000 papers. These Editors work out of a sense of altruism and commitment to Hospital Medicine and have made huge individual contributions to JHM through their reviewing expertise and ensuring that the editorial sense for JHM is as broad and innovative as our field.

Finally, I must thank my core team of Senior Deputy Editors who have shouldered the majority of editorial work, mentored Editors (including me) and Peer Reviewers, and provided strategic guidance.

How peer-reviewed journals are published is changing rapidly. Setting aside the questions of how we consume our medical literature and the transition from paper to digital, old financial models depending on subscriptions and advertising are either dying or evolving into something very different. The challenge is that the new model is very unclear and the old model based on ads and subscriptions is clearly nonviable but is the primary way to support the work of producing a journal. Moving from the current model to one based on clicks, views, or downloads will come down to who will derive benefit from those clicks/downloads, who will be willing to pay to read and learn from the work of authors, or who views that activity as being worthy enough advertise somewhere in that process or to monetize the data garnered from readers’ activities. In addition, many journals, including JHM, are supported by professional societies. While professional societies have a goal to serve their members, the goal of the peer-reviewed journal is to independently and broadly represent the field. One must reflect the other, but space between the two will always be required.

The speed with which research takes place is too slow, and the process of getting evidence into print (much less adopted) is even slower. But, this too is changing; the role of peer review and the publication process is evolving. In order to speed the potential discovery of new innovations, prepublication repositories (such as BioRxViv) are gaining popularity; well-publicized scandals around peer reviewing rings 1 have not gone unnoticed, and have produced greater interest in using prepublication comments and online discussions as early forms of review. As a result, the disintermediation between scientist and ‘evidence’ is paralleling the disintermediation between events and messengers elsewhere. One need only review Twitter for a moment to get a sense for how crowdsourcing can lead to evidence (or news) generation for good or ill. I agree that while the end of journals (as we understand them now) is upon us, these are also opportunities for JHM as it enters its new phase and a place for leadership. 2

I am proud of what we have done at JHM in the last seven years. We have grown substantially. We have innovated and provided great service to our authors and the field of Hospital Medicine. Our growth and forward-looking approaches to social media and our digital footprint put the journal on a great path towards adapting to the trends in Hospital Medicine research and peer-reviewed publishing. Our focus on being doctors who care for patients and our teams—not just doctors who care for hospitals—is supporting the field and our practice. I look forward to seeing where JHM goes next.

 

 

 

After seven years at the helm of the Journal of Hospital Medicine, I am both pleased to hand over the reins and sad to let them go. My time as Editor in Chief has been wonderful, challenging, and fulfilling.

When I began my tenure, JHM managed approximately 350 papers annually, and published 10 times per year. We had no social media presence, a developing editorial sense (and developing Editor in Chief), and a pool of hard-working and passionate Editors. As of this year, we have handled more than 700 papers and are publishing content monthly, online only, and online first. Our dedicated team is deeply passionate about making every paper better through interaction with the authors—whether we accept it for publication or not.

JHM has added a presence on Facebook and Twitter, launched a Twitter Journal Club as a regular offering (#JHMChat), added visual abstracts to our Tweets and Facebook postings, and researched how these novel approaches increase not only the Journal’s social media presence but also its public face. Our efforts in social media were trendsetting in peer-reviewed literature, and the Editors who lead those efforts—Vineet Arora and Charlie Wray—are asked to consult for other journals regularly.

We launched two new series— Choosing Wisely®: Next Steps, and Choosing Wisely®: Things We Do For No Reason—with help from the ABIM Foundation and visionary Editors, Andy Masica, Ann Sheehy, and Lenny Feldman. These papers have pushed Hospitalists and Hospital Medicine to think carefully about the simple things we do every day, to think broadly about how to move past the initial ‘low-hanging fruit’ of value improvement, and point us towards policy and intervention approaches that are disruptive rather than incremental.

A special thank you to Som Mookherjee, Brian Harte, Dan Hunt, and Read Pierce who ably developed the Clinical Care Conundrums and Review series. They are assisted by teams of national correspondents and many contributors who’ve submitted work for those series.

I have been blessed by a team of more than a dozen Associate Editors who have ably, expeditiously, and collegially managed more than 2,000 papers. These Editors work out of a sense of altruism and commitment to Hospital Medicine and have made huge individual contributions to JHM through their reviewing expertise and ensuring that the editorial sense for JHM is as broad and innovative as our field.

Finally, I must thank my core team of Senior Deputy Editors who have shouldered the majority of editorial work, mentored Editors (including me) and Peer Reviewers, and provided strategic guidance.

How peer-reviewed journals are published is changing rapidly. Setting aside the questions of how we consume our medical literature and the transition from paper to digital, old financial models depending on subscriptions and advertising are either dying or evolving into something very different. The challenge is that the new model is very unclear and the old model based on ads and subscriptions is clearly nonviable but is the primary way to support the work of producing a journal. Moving from the current model to one based on clicks, views, or downloads will come down to who will derive benefit from those clicks/downloads, who will be willing to pay to read and learn from the work of authors, or who views that activity as being worthy enough advertise somewhere in that process or to monetize the data garnered from readers’ activities. In addition, many journals, including JHM, are supported by professional societies. While professional societies have a goal to serve their members, the goal of the peer-reviewed journal is to independently and broadly represent the field. One must reflect the other, but space between the two will always be required.

The speed with which research takes place is too slow, and the process of getting evidence into print (much less adopted) is even slower. But, this too is changing; the role of peer review and the publication process is evolving. In order to speed the potential discovery of new innovations, prepublication repositories (such as BioRxViv) are gaining popularity; well-publicized scandals around peer reviewing rings 1 have not gone unnoticed, and have produced greater interest in using prepublication comments and online discussions as early forms of review. As a result, the disintermediation between scientist and ‘evidence’ is paralleling the disintermediation between events and messengers elsewhere. One need only review Twitter for a moment to get a sense for how crowdsourcing can lead to evidence (or news) generation for good or ill. I agree that while the end of journals (as we understand them now) is upon us, these are also opportunities for JHM as it enters its new phase and a place for leadership. 2

I am proud of what we have done at JHM in the last seven years. We have grown substantially. We have innovated and provided great service to our authors and the field of Hospital Medicine. Our growth and forward-looking approaches to social media and our digital footprint put the journal on a great path towards adapting to the trends in Hospital Medicine research and peer-reviewed publishing. Our focus on being doctors who care for patients and our teams—not just doctors who care for hospitals—is supporting the field and our practice. I look forward to seeing where JHM goes next.

 

 

 

References

1. Retraction Watch. BioMedCentral retracting 43 papers for fake peer reviews. March 26, 2015; http://retractionwatch.com/2015/03/26/biomed-central-retracting-43-papers-for-fake-peer-review/. Accessed November 12, 2018.
2. Krumholz HM. The End of Journals. Circ Cardiovasc Qual Outcomes. 2015;8(6):533-534. doi: 10.1161/CIRCOUTCOMES.115.002415. PubMed

References

1. Retraction Watch. BioMedCentral retracting 43 papers for fake peer reviews. March 26, 2015; http://retractionwatch.com/2015/03/26/biomed-central-retracting-43-papers-for-fake-peer-review/. Accessed November 12, 2018.
2. Krumholz HM. The End of Journals. Circ Cardiovasc Qual Outcomes. 2015;8(6):533-534. doi: 10.1161/CIRCOUTCOMES.115.002415. PubMed

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Andrew D. Auerbach MD MPH, UCSF Division of Hospital Medicine, UCSF Box 0131, San Francisco, CA 94143-0131; Telephone: 415-502-1412, Fax: 415-514-2094; E-mail: [email protected]
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Barriers to Early Hospital Discharge: A Cross-Sectional Study at Five Academic Hospitals

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Hospital discharges frequently occur in the afternoon or evening hours.1-5 Late discharges can adversely affect patient flow throughout the hospital,3,6-9 which, in turn, can result in delays in care,10-16 more medication errors,17 increased mortality,18-20 longer lengths of stay,20-22 higher costs,23 and lower patient satisfaction.24

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,25 using checklists,1,25 team huddles,2 providing real-time feedback to unit staff,1 and employing multidisciplinary teamwork.1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

METHODS

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

 

 

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.27 Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

RESULTS

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.



Over the course of the three surveys, 949 patients were identified as being definite discharges at any time point, and the large majority of these (863, 91%) were discharged on the day of the survey. The median (IQR) time that the discharge orders were written was 11:50 am (10:35 am, 1:45 pm).

During the initial morning survey, 314 patients were identified as being definite discharges for that day (representing approximately 6% of the total number of patients being cared for, or 33% of the patients identified as definite discharges throughout the day). Of these, the physicians thought that 44 (<1% of the total number of patients being cared for on the services) could have been discharged on the previous day. The most frequent reasons cited for why these patients were not discharged on the previous day were “Patient did not want to leave” (n = 15, 34%), “Too late in the day” (n = 10, 23%), and “No ride” (n = 9, 20%). The remaining 10 patients (23%) had a variety of reasons related to system or social issues (ie, shelter not available, miscommunication).

At the morning time point, the most common barriers to discharge identified were that the physicians had not finished rounding on their team of patients and that the housestaff needed to staff their patients with their attending. At noon, caring for other patients and tending to the discharge processes were most commonly cited, and in the afternoon, the most common barriers were that the physicians were in the process of completing the discharge paperwork for those patients or were discharging other patients (Table 2). When comparing barriers on teaching to nonteaching teams, a higher proportion of teaching teams were still rounding on all patients and were working on discharge paperwork at the second survey. Barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied (data not shown).


The physicians identified 1,237 patients at any time point as being possible discharges during the day of the survey and these had a mean (±SD) of 1.3 (±0.5) barriers cited for why these patients were possible rather than definite discharges. The most common were that clinical improvement was needed, one or more pending issues related to their care needed to be resolved, and/or awaiting pending test results. The need to see clinical improvement generally decreased throughout the day as did the need to staff patients with an attending physician, but barriers related to consultant recommendations or completing procedures increased (Table 3). Of the 1,237 patients ever identified as possible discharges, 594 (48%) became a definite discharge by the third call and 444 (36%) became a no discharge as their final status. As with definite discharges, barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied.


Among the 949 and 1,237 patients who were ever identified as definite or possible discharges, respectively, at any time point during the study day, 28 (3%) and 444 (36%), respectively, had their discharge status changed to no discharge, most commonly because their clinical condition either worsened or expected improvements did not occur or that barriers pertaining to social work, physical therapy, or occupational therapy were not resolved.

The median time that the discharge orders were entered into the electronic medical record was 43 minutes earlier if patients were on teams with a lower versus a higher starting census (P = .0003), 48 minutes earlier if they were seen by physicians whose rounding style was to see patients first who potentially could be discharged (P = .0026), and 58 minutes earlier if they were on nonteaching versus teaching services (P < .0001; Table 4). For every one-person increase in census, the discharge order time increased by 6 minutes (β = 5.6, SE = 1.6, P = .0003).

 

 

DISCUSSION

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.30 Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.25 Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,2,4 but the overall length of stay either did not decrease25 or increased31 in others. Werthheimer et al.1 did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.33 found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.29 found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

 

 

Disclosures

The authors report no conflicts of interest relevant to this work.

 

Files
References

1. Wertheimer B, Jacobs RE, Bailey M, et al. Discharge before noon: an achievable hospital goal. J Hosp Med. 2014;9(4):210-214. doi: 10.1002/jhm.2154. PubMed
2. Kane M, Weinacker A, Arthofer R, et al. A multidisciplinary initiative to increase inpatient discharges before noon. J Nurs Adm. 2016;46(12):630-635. doi: 10.1097/NNA.0000000000000418. PubMed
3. Khanna S, Sier D, Boyle J, Zeitz K. Discharge timeliness and its impact on hospital crowding and emergency department flow performance. Emerg Med Australas. 2016;28(2):164-170. doi: 10.1111/1742-6723.12543. PubMed
4. Kravet SJ, Levine RB, Rubin HR, Wright SM. Discharging patients earlier in the day: a concept worth evaluating. Health Care Manag (Frederick). 2007;26:142-146. doi: 10.1097/01.HCM.0000268617.33491.60. PubMed
5. Khanna S, Boyle J, Good N, Lind J. Impact of admission and discharge peak times on hospital overcrowding. Stud Health Technol Inform. 2011;168:82-88. doi: 10.3233/978-1-60750-791-8-82. PubMed
6. McGowan JE, Truwit JD, Cipriano P, et al. Operating room efficiency and hospital capacity: factors affecting operating room use during maximum hospital census. J Am Coll Surg. 2007;204(5):865-871; discussion 71-72. doi: 10.1016/j.jamcollsurg.2007.01.052 PubMed
7. Khanna S, Boyle J, Good N, Lind J. Early discharge and its effect on ED length of stay and access block. Stud Health Technol Inform. 2012;178:92-98. doi: 10.3233/978-1-61499-078-9-92 PubMed
8. Powell ES, Khare RK, Venkatesh AK, Van Roo BD, Adams JG, Reinhardt G. The relationship between inpatient discharge timing and emergency department boarding. J Emerg Med. 2012;42(2):186-196. doi: 10.1016/j.jemermed.2010.06.028. PubMed
9. Wertheimer B, Jacobs RE, Iturrate E, Bailey M, Hochman K. Discharge before noon: Effect on throughput and sustainability. J Hosp Med. 2015;10(10):664-669. doi: 10.1002/jhm.2412. PubMed
10. Sikka R, Mehta S, Kaucky C, Kulstad EB. ED crowding is associated with an increased time to pneumonia treatment. Am J Emerg Med. 2010;28(7):809-812. doi: 10.1016/j.ajem.2009.06.023. PubMed
11. Coil CJ, Flood JD, Belyeu BM, Young P, Kaji AH, Lewis RJ. The effect of emergency department boarding on order completion. Ann Emerg Med. 2016;67:730-736 e2. doi: 10.1016/j.annemergmed.2015.09.018. PubMed
12. Gaieski DF, Agarwal AK, Mikkelsen ME, et al. The impact of ED crowding on early interventions and mortality in patients with severe sepsis. Am J Emerg Med. 2017;35:953-960. doi: 10.1016/j.ajem.2017.01.061. PubMed
13. Pines JM, Localio AR, Hollander JE, et al. The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia. Ann Emerg Med. 2007;50(5):510-516. doi: 10.1016/j.annemergmed.2007.07.021. PubMed
14. Hwang U, Richardson L, Livote E, Harris B, Spencer N, Sean Morrison R. Emergency department crowding and decreased quality of pain care. Acad Emerg Med. 2008;15:1248-1255. doi: 10.1111/j.1553-2712.2008.00267.x. PubMed
15. Mills AM, Shofer FS, Chen EH, Hollander JE, Pines JM. The association between emergency department crowding and analgesia administration in acute abdominal pain patients. Acad Emerg Med. 2009;16:603-608. doi: 10.1111/j.1553-2712.2009.00441.x. PubMed
16. Pines JM, Shofer FS, Isserman JA, Abbuhl SB, Mills AM. The effect of emergency department crowding on analgesia in patients with back pain in two hospitals. Acad Emerg Med. 2010;17(3):276-283. doi: 10.1111/j.1553-2712.2009.00676.x. PubMed
17. Kulstad EB, Sikka R, Sweis RT, Kelley KM, Rzechula KH. ED overcrowding is associated with an increased frequency of medication errors. Am J Emerg Med. 2010;28:304-309. doi: 10.1016/j.ajem.2008.12.014. PubMed
18. Richardson DB. Increase in patient mortality at 10 days associated with emergency department overcrowding. Med J Aust. 2006;184(5):213-216. PubMed
19. Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med. 2008;52(2):126-136. doi: 10.1016/j.annemergmed.2008.03.014. PubMed
20. Singer AJ, Thode HC, Jr., Viccellio P, Pines JM. The association between length of emergency department boarding and mortality. Acad Emerg Med. 2011;18(12):1324-1329. doi: 10.1111/j.1553-2712.2011.01236.x. PubMed
21. White BA, Biddinger PD, Chang Y, Grabowski B, Carignan S, Brown DF. Boarding inpatients in the emergency department increases discharged patient length of stay. J Emerg Med. 2013;44(1):230-235. doi: 10.1016/j.jemermed.2012.05.007. PubMed
22. Forster AJ, Stiell I, Wells G, Lee AJ, van Walraven C. The effect of hospital occupancy on emergency department length of stay and patient disposition. Acad Emerg Med. 2003;10(2):127-133. doi: 10.1197/aemj.10.2.127. PubMed
23. Foley M, Kifaieh N, Mallon WK. Financial impact of emergency department crowding. West J Emerg Med. 2011;12(2):192-197. PubMed
24. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med. 2008;15(9):825-831. doi: 10.1111/j.1553-2712.2008.00200.x. PubMed
25. Durvasula R, Kayihan A, Del Bene S, et al. A multidisciplinary care pathway significantly increases the number of early morning discharges in a large academic medical center. Qual Manag Health Care. 2015;24:45-51. doi: 10.1097/QMH.0000000000000049. PubMed
26. Cho HJ, Desai N, Florendo A, et al. E-DIP: Early Discharge Project. A Model for Throughput and Early Discharge for 1-Day Admissions. BMJ Qual Improv Rep. 2016;5(1): pii: u210035.w4128. doi: 10.1136/bmjquality.u210035.w4128. PubMed
27. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. doi: 10.1016/j.jbi.2008.08.010. PubMed
28. Patel H, Fang MC, Mourad M, et al. Hospitalist and internal medicine leaders’ perspectives of early discharge challenges at academic medical centers. J Hosp Med. 2018;13(6):388-391. doi: 10.12788/jhm.2885. PubMed
29. Minichiello TM, Auerbach AD, Wachter RM. Caregiver perceptions of the reasons for delayed hospital discharge. Eff Clin Pract. 2001;4(6):250-255. PubMed
30. Beck MJ, Okerblom D, Kumar A, Bandyopadhyay S, Scalzi LV. Lean intervention improves patient discharge times, improves emergency department throughput and reduces congestion. Hosp Pract (1995). 2016;44(5):252-259. doi: 10.1080/21548331.2016.1254559. PubMed
31. Rajkomar A, Valencia V, Novelero M, Mourad M, Auerbach A. The association between discharge before noon and length of stay in medical and surgical patients. J Hosp Med. 2016;11(12):859-861. doi: 10.1002/jhm.2529. PubMed
32. Shine D. Discharge before noon: an urban legend. Am J Med. 2015;128(5):445-446. doi: 10.1016/j.amjmed.2014.12.011. PubMed
<--pagebreak-->33. Khanna S, Boyle J, Good N, Lind J. Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block. Emerg Med Australas. 2012;24(5):510-517. doi: 10.1111/j.1742-6723.2012.01587.x. PubMed

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Related Articles

Hospital discharges frequently occur in the afternoon or evening hours.1-5 Late discharges can adversely affect patient flow throughout the hospital,3,6-9 which, in turn, can result in delays in care,10-16 more medication errors,17 increased mortality,18-20 longer lengths of stay,20-22 higher costs,23 and lower patient satisfaction.24

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,25 using checklists,1,25 team huddles,2 providing real-time feedback to unit staff,1 and employing multidisciplinary teamwork.1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

METHODS

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

 

 

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.27 Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

RESULTS

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.



Over the course of the three surveys, 949 patients were identified as being definite discharges at any time point, and the large majority of these (863, 91%) were discharged on the day of the survey. The median (IQR) time that the discharge orders were written was 11:50 am (10:35 am, 1:45 pm).

During the initial morning survey, 314 patients were identified as being definite discharges for that day (representing approximately 6% of the total number of patients being cared for, or 33% of the patients identified as definite discharges throughout the day). Of these, the physicians thought that 44 (<1% of the total number of patients being cared for on the services) could have been discharged on the previous day. The most frequent reasons cited for why these patients were not discharged on the previous day were “Patient did not want to leave” (n = 15, 34%), “Too late in the day” (n = 10, 23%), and “No ride” (n = 9, 20%). The remaining 10 patients (23%) had a variety of reasons related to system or social issues (ie, shelter not available, miscommunication).

At the morning time point, the most common barriers to discharge identified were that the physicians had not finished rounding on their team of patients and that the housestaff needed to staff their patients with their attending. At noon, caring for other patients and tending to the discharge processes were most commonly cited, and in the afternoon, the most common barriers were that the physicians were in the process of completing the discharge paperwork for those patients or were discharging other patients (Table 2). When comparing barriers on teaching to nonteaching teams, a higher proportion of teaching teams were still rounding on all patients and were working on discharge paperwork at the second survey. Barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied (data not shown).


The physicians identified 1,237 patients at any time point as being possible discharges during the day of the survey and these had a mean (±SD) of 1.3 (±0.5) barriers cited for why these patients were possible rather than definite discharges. The most common were that clinical improvement was needed, one or more pending issues related to their care needed to be resolved, and/or awaiting pending test results. The need to see clinical improvement generally decreased throughout the day as did the need to staff patients with an attending physician, but barriers related to consultant recommendations or completing procedures increased (Table 3). Of the 1,237 patients ever identified as possible discharges, 594 (48%) became a definite discharge by the third call and 444 (36%) became a no discharge as their final status. As with definite discharges, barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied.


Among the 949 and 1,237 patients who were ever identified as definite or possible discharges, respectively, at any time point during the study day, 28 (3%) and 444 (36%), respectively, had their discharge status changed to no discharge, most commonly because their clinical condition either worsened or expected improvements did not occur or that barriers pertaining to social work, physical therapy, or occupational therapy were not resolved.

The median time that the discharge orders were entered into the electronic medical record was 43 minutes earlier if patients were on teams with a lower versus a higher starting census (P = .0003), 48 minutes earlier if they were seen by physicians whose rounding style was to see patients first who potentially could be discharged (P = .0026), and 58 minutes earlier if they were on nonteaching versus teaching services (P < .0001; Table 4). For every one-person increase in census, the discharge order time increased by 6 minutes (β = 5.6, SE = 1.6, P = .0003).

 

 

DISCUSSION

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.30 Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.25 Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,2,4 but the overall length of stay either did not decrease25 or increased31 in others. Werthheimer et al.1 did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.33 found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.29 found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

 

 

Disclosures

The authors report no conflicts of interest relevant to this work.

 

Hospital discharges frequently occur in the afternoon or evening hours.1-5 Late discharges can adversely affect patient flow throughout the hospital,3,6-9 which, in turn, can result in delays in care,10-16 more medication errors,17 increased mortality,18-20 longer lengths of stay,20-22 higher costs,23 and lower patient satisfaction.24

Various interventions have been employed in the attempts to find ways of moving discharge times to earlier in the day, including preparing the discharge paperwork and medications the previous night,25 using checklists,1,25 team huddles,2 providing real-time feedback to unit staff,1 and employing multidisciplinary teamwork.1,2,6,25,26

The purpose of this study was to identify and determine the relative frequency of barriers to writing discharge orders in the hopes of identifying issues that might be addressed by targeted interventions. We also assessed the effects of daily team census, patients being on teaching versus nonteaching services, and how daily rounds were structured at the time that the discharge orders were written.

METHODS

Study Design, Setting, and Participants

We conducted a prospective, cross-sectional survey of house-staff and attending physicians on general medicine teaching and nonteaching services from November 13, 2014, through May 31, 2016. The study was conducted at the following five hospitals: Denver Health Medical Center (DHMC) and Presbyterian/Saint Luke’s Medical Center (PSL) in Denver, Colorado; Ronald Reagan University (UCLA) and Los Angeles County/University of Southern California Medical Center (LAC+USC) in Los Angeles, California; and Harborview Medical Center (HMC) in Seattle, Washington. The study was approved by the Colorado Multi-Institutional Review Board as well as by the review boards of the other participating sites.

Data Collection

The results of the focus groups composed of attending physicians at DHMC were used to develop our initial data collection template. Additional sites joining the study provided feedback, leading to modifications (Appendix 1).

Physicians were surveyed at three different time points on study days that were selected according to the convenience of the investigators. The sampling occurred only on weekdays and was done based on the investigators’ availability. Investigators would attempt to survey as many teams as they were able to but, secondary to feasibility, not all teams could be surveyed on study days. The specific time points varied as a function of physician workflows but were standardized as much as possible to occur in the early morning, around noon, and midafternoon on weekdays. Physicians were contacted either in person or by telephone for verbal consent prior to administering the first survey. All general medicine teams were eligible. For teaching teams, the order of contact was resident, intern, and then attending based on which physician was available at the time of the survey and on which member of the team was thought to know the patients the best. For the nonteaching services, the attending physicians were contacted.

During the initial survey, the investigators assessed the provider role (ie, attending or housestaff), whether the service was a teaching or a nonteaching service, and the starting patient census on that service primarily based on interviewing the provider of record for the team and looking at team census lists. Physicians were asked about their rounding style (ie, sickest patients first, patients likely to be discharged first, room-by-room, most recently admitted patients first, patients on the team the longest, or other) and then to identify all patients they thought would be definite discharges sometime during the day of the survey. Definite discharges were defined as patients whom the provider thought were either currently ready for discharge or who had only minor barriers that, if unresolved, would not prevent same-day discharge. They were asked if the discharge order had been entered and, if not, what was preventing them from doing so, if the discharge could in their opinion have occurred the day prior and, if so, why this did not occur. We also obtained the date and time of the admission and discharge orders, the actual discharge time, as well as the length of stay either through chart review (majority of sites) or from data warehouses (Denver Health and Presbyterian St. Lukes had length of stay data retrieved from their data warehouse).

Physicians were also asked to identify all patients whom they thought might possibly be discharged that day. Possible discharges were defined as patients with barriers to discharge that, if unresolved, would prevent same-day discharge. For each of these, the physicians were asked to list whatever issues needed to be resolved prior to placing the discharge order (Appendix 1).

The second survey was administered late morning on the same day, typically between 11 am and 12 pm. In this survey, the physicians were asked to reassess the patients previously classified as definite and possible discharges for changes in status and/or barriers and to identify patients who had become definite or possible discharges since the earlier survey. Newly identified possible or definite discharges were evaluated in a similar manner as the initial survey.

The third survey was administered midafternoon, typically around 3 PM similar to the first two surveys, with the exception that the third survey did not attempt to identify new definite or possible discharges.

 

 

Sample Size

We stopped collecting data after obtaining a convenience sample of 5% of total discharges at each study site or on the study end date, which was May 31, 2016, whichever came first.

Data Analysis

Data were collected and managed using a secure, web-based application electronic data capture tool (REDCap), hosted at Denver Health. REDCap (Research Electronic Data Capture, Nashville, Tennessee) is designed to support data collection for research studies.27 Data were then analyzed using SAS Enterprise Guide 5.1 (SAS Institute, Inc., Cary, North Carolina). All data entered into REDCap were reviewed by the principal investigator to ensure that data were not missing, and when there were missing data, a query was sent to verify if the data were retrievable. If retrievable, then the data would be entered. The volume of missing data that remained is described in our results.

Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR) based on tests of normality. Differences in the time that the discharge orders were placed in the electronic medical record according to morning patient census, teaching versus nonteaching service, and rounding style were compared using the Wilcoxon rank sum test. Linear regression was used to evaluate the effect of patient census on discharge order time. P < .05 was considered as significant.

RESULTS

We conducted 1,584 patient evaluations through surveys of 254 physicians over 156 days. Given surveys coincided with the existing work we had full participation (ie, 100% participation) and no dropout during the study days. Median (IQR) survey time points were 8:30 am (7:51 am, 9:12 am), 11:45 am (11:30 am, 12:17 pm), and 3:20 pm (3:00 pm, 4:06 pm).

The characteristics of the five hospitals participating in the study, the patients’ final discharge status, the types of physicians surveyed, the services on which they were working, the rounding styles employed, and the median starting daily census are summarized in Table 1. The majority of the physicians surveyed were housestaff working on teaching services, and only a small minority structured rounds such that patients ready for discharge were seen first.



Over the course of the three surveys, 949 patients were identified as being definite discharges at any time point, and the large majority of these (863, 91%) were discharged on the day of the survey. The median (IQR) time that the discharge orders were written was 11:50 am (10:35 am, 1:45 pm).

During the initial morning survey, 314 patients were identified as being definite discharges for that day (representing approximately 6% of the total number of patients being cared for, or 33% of the patients identified as definite discharges throughout the day). Of these, the physicians thought that 44 (<1% of the total number of patients being cared for on the services) could have been discharged on the previous day. The most frequent reasons cited for why these patients were not discharged on the previous day were “Patient did not want to leave” (n = 15, 34%), “Too late in the day” (n = 10, 23%), and “No ride” (n = 9, 20%). The remaining 10 patients (23%) had a variety of reasons related to system or social issues (ie, shelter not available, miscommunication).

At the morning time point, the most common barriers to discharge identified were that the physicians had not finished rounding on their team of patients and that the housestaff needed to staff their patients with their attending. At noon, caring for other patients and tending to the discharge processes were most commonly cited, and in the afternoon, the most common barriers were that the physicians were in the process of completing the discharge paperwork for those patients or were discharging other patients (Table 2). When comparing barriers on teaching to nonteaching teams, a higher proportion of teaching teams were still rounding on all patients and were working on discharge paperwork at the second survey. Barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied (data not shown).


The physicians identified 1,237 patients at any time point as being possible discharges during the day of the survey and these had a mean (±SD) of 1.3 (±0.5) barriers cited for why these patients were possible rather than definite discharges. The most common were that clinical improvement was needed, one or more pending issues related to their care needed to be resolved, and/or awaiting pending test results. The need to see clinical improvement generally decreased throughout the day as did the need to staff patients with an attending physician, but barriers related to consultant recommendations or completing procedures increased (Table 3). Of the 1,237 patients ever identified as possible discharges, 594 (48%) became a definite discharge by the third call and 444 (36%) became a no discharge as their final status. As with definite discharges, barriers cited by sites were similar; however, the frequency at which the barriers were mentioned varied.


Among the 949 and 1,237 patients who were ever identified as definite or possible discharges, respectively, at any time point during the study day, 28 (3%) and 444 (36%), respectively, had their discharge status changed to no discharge, most commonly because their clinical condition either worsened or expected improvements did not occur or that barriers pertaining to social work, physical therapy, or occupational therapy were not resolved.

The median time that the discharge orders were entered into the electronic medical record was 43 minutes earlier if patients were on teams with a lower versus a higher starting census (P = .0003), 48 minutes earlier if they were seen by physicians whose rounding style was to see patients first who potentially could be discharged (P = .0026), and 58 minutes earlier if they were on nonteaching versus teaching services (P < .0001; Table 4). For every one-person increase in census, the discharge order time increased by 6 minutes (β = 5.6, SE = 1.6, P = .0003).

 

 

DISCUSSION

The important findings of this study are that (1) the large majority of issues thought to delay discharging patients identified as definite discharges were related to physicians caring for other patients on their team, (2) although 91% of patients ever identified as being definite discharges were discharged on the day of the survey, only 48% of those identified as possible discharges became definite discharges by the afternoon time point, largely because the anticipated clinical improvement did not occur or care being provided by ancillary services had not been completed, and (3) discharge orders on patients identified as definite discharges were written on average 50 minutes earlier by physicians on teams with a smaller starting patient census, on nonteaching services, or when the rounding style was to see patients ready for discharges first.

Previous research has reported that physician-perceived barriers to discharge were extrinsic to providers and even extrinsic to the hospital setting (eg, awaiting subacute nursing placement and transportation).28,29 However, many of the barriers that we identified were related directly to the providers’ workload and rounding styles and whether the patients were on teaching versus nonteaching services. We also found that delays in the ability of hospital services to complete care also contributed to delayed discharges.

Our observational data suggest that delays resulting from caring for other patients might be reduced by changing rounding styles such that patients ready for discharge are seen first and are discharged prior to seeing other patients on the team, as previously reported by Beck et al.30 Intuitively, this would seem to be a straightforward way of freeing up beds earlier in the day, but such a change will, of necessity, lead to delaying care for other patients, which, in turn, could increase their length of stays. Durvasula et al. suggested that discharges could be moved to earlier in the day by completing orders and paperwork the day prior to discharge.25 Such an approach might be effective on an Obstetrical or elective Orthopedic service on which patients predictably are hospitalized for a fixed number of days (or even hours) but may be less relevant to patients on internal medicine services where lengths of stay are less predictable. Interventions to improve discharge times have resulted in earlier discharge times in some studies,2,4 but the overall length of stay either did not decrease25 or increased31 in others. Werthheimer et al.1 did find earlier discharge times, but other interventions also occurred during the study period (eg, extending social work services to include weekends).1,32

We found that discharge times were approximately 50 minutes earlier on teams with a smaller starting census, on nonteaching compared with teaching services, or when the attending’s rounding style was to see patients ready for discharges first. Although 50 minutes may seem like a small change in discharge time, Khanna et al.33 found that when discharges occur even 1 hour earlier, hospital overcrowding is reduced. To have a lower team census would require having more teams and more providers to staff these teams, raising cost-effectiveness concerns. Moving to more nonteaching services could represent a conflict with respect to one of the missions of teaching hospitals and raises a cost-benefit issue as several teaching hospitals receive substantial funding in support of their teaching activities and housestaff would have to be replaced with more expensive providers.

Delays attributable to ancillary services indicate imbalances between demand and availability of these services. Inappropriate demand and inefficiencies could be reduced by systems redesign, but in at least some instances, additional resources will be needed to add staff, increase space, or add additional equipment.

Our study has several limitations. First, we surveyed only physicians working in university-affiliated hospitals, and three of these were public safety-net hospitals. Accordingly, our results may not be generalizable to different patient populations. Second, we surveyed only physicians, and Minichiello et al.29 found that barriers to discharge perceived by physicians were different from those of other staff. Third, our data were observational and were collected only on weekdays. Fourth, we did not differentiate interns from residents, and thus, potentially the level of training could have affected these results. Similarly, the decision for a “possible” and a “definite” discharge is likely dependent on the knowledge base of the participant, such that less experienced participants may have had differing perspectives than someone with more experience. Fifth, the sites did vary based on the infrastructure and support but also had several similarities. All sites had social work and case management involved in care, although at some sites, they were assigned according to team and at others according to geographic location. Similarly, rounding times varied. Most of the services surveyed did not utilize advanced practice providers (the exception was the nonteaching services at Denver Health, and their presence was variable). These differences in staffing models could also have affected these results.

Our study also has a number of strengths. First, we assessed the barriers at five different hospitals. Second, we collected real-time data related to specific barriers at multiple time points throughout the day, allowing us to assess the dynamic nature of identifying patients as being ready or nearly ready for discharge. Third, we assessed the perceptions of barriers to discharge from physicians working on teaching as well as nonteaching services and from physicians utilizing a variety of rounding styles. Fourth, we had a very high participation rate (100%), probably due to the fact that our study was strategically aligned with participants’ daily work activities.

In conclusion, we found two distinct categories of issues that physicians perceived as most commonly delaying writing discharge orders on their patients. The first pertained to patients thought to definitely be ready for discharge and was related to the physicians having to care for other patients on their team. The second pertained to patients identified as possibly ready for discharge and was related to the need for care to be completed by a variety of ancillary services. Addressing each of these barriers would require different interventions and a need to weigh the potential improvements that could be achieved against the increased costs and/or delays in care for other patients that may result.

 

 

Disclosures

The authors report no conflicts of interest relevant to this work.

 

References

1. Wertheimer B, Jacobs RE, Bailey M, et al. Discharge before noon: an achievable hospital goal. J Hosp Med. 2014;9(4):210-214. doi: 10.1002/jhm.2154. PubMed
2. Kane M, Weinacker A, Arthofer R, et al. A multidisciplinary initiative to increase inpatient discharges before noon. J Nurs Adm. 2016;46(12):630-635. doi: 10.1097/NNA.0000000000000418. PubMed
3. Khanna S, Sier D, Boyle J, Zeitz K. Discharge timeliness and its impact on hospital crowding and emergency department flow performance. Emerg Med Australas. 2016;28(2):164-170. doi: 10.1111/1742-6723.12543. PubMed
4. Kravet SJ, Levine RB, Rubin HR, Wright SM. Discharging patients earlier in the day: a concept worth evaluating. Health Care Manag (Frederick). 2007;26:142-146. doi: 10.1097/01.HCM.0000268617.33491.60. PubMed
5. Khanna S, Boyle J, Good N, Lind J. Impact of admission and discharge peak times on hospital overcrowding. Stud Health Technol Inform. 2011;168:82-88. doi: 10.3233/978-1-60750-791-8-82. PubMed
6. McGowan JE, Truwit JD, Cipriano P, et al. Operating room efficiency and hospital capacity: factors affecting operating room use during maximum hospital census. J Am Coll Surg. 2007;204(5):865-871; discussion 71-72. doi: 10.1016/j.jamcollsurg.2007.01.052 PubMed
7. Khanna S, Boyle J, Good N, Lind J. Early discharge and its effect on ED length of stay and access block. Stud Health Technol Inform. 2012;178:92-98. doi: 10.3233/978-1-61499-078-9-92 PubMed
8. Powell ES, Khare RK, Venkatesh AK, Van Roo BD, Adams JG, Reinhardt G. The relationship between inpatient discharge timing and emergency department boarding. J Emerg Med. 2012;42(2):186-196. doi: 10.1016/j.jemermed.2010.06.028. PubMed
9. Wertheimer B, Jacobs RE, Iturrate E, Bailey M, Hochman K. Discharge before noon: Effect on throughput and sustainability. J Hosp Med. 2015;10(10):664-669. doi: 10.1002/jhm.2412. PubMed
10. Sikka R, Mehta S, Kaucky C, Kulstad EB. ED crowding is associated with an increased time to pneumonia treatment. Am J Emerg Med. 2010;28(7):809-812. doi: 10.1016/j.ajem.2009.06.023. PubMed
11. Coil CJ, Flood JD, Belyeu BM, Young P, Kaji AH, Lewis RJ. The effect of emergency department boarding on order completion. Ann Emerg Med. 2016;67:730-736 e2. doi: 10.1016/j.annemergmed.2015.09.018. PubMed
12. Gaieski DF, Agarwal AK, Mikkelsen ME, et al. The impact of ED crowding on early interventions and mortality in patients with severe sepsis. Am J Emerg Med. 2017;35:953-960. doi: 10.1016/j.ajem.2017.01.061. PubMed
13. Pines JM, Localio AR, Hollander JE, et al. The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia. Ann Emerg Med. 2007;50(5):510-516. doi: 10.1016/j.annemergmed.2007.07.021. PubMed
14. Hwang U, Richardson L, Livote E, Harris B, Spencer N, Sean Morrison R. Emergency department crowding and decreased quality of pain care. Acad Emerg Med. 2008;15:1248-1255. doi: 10.1111/j.1553-2712.2008.00267.x. PubMed
15. Mills AM, Shofer FS, Chen EH, Hollander JE, Pines JM. The association between emergency department crowding and analgesia administration in acute abdominal pain patients. Acad Emerg Med. 2009;16:603-608. doi: 10.1111/j.1553-2712.2009.00441.x. PubMed
16. Pines JM, Shofer FS, Isserman JA, Abbuhl SB, Mills AM. The effect of emergency department crowding on analgesia in patients with back pain in two hospitals. Acad Emerg Med. 2010;17(3):276-283. doi: 10.1111/j.1553-2712.2009.00676.x. PubMed
17. Kulstad EB, Sikka R, Sweis RT, Kelley KM, Rzechula KH. ED overcrowding is associated with an increased frequency of medication errors. Am J Emerg Med. 2010;28:304-309. doi: 10.1016/j.ajem.2008.12.014. PubMed
18. Richardson DB. Increase in patient mortality at 10 days associated with emergency department overcrowding. Med J Aust. 2006;184(5):213-216. PubMed
19. Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med. 2008;52(2):126-136. doi: 10.1016/j.annemergmed.2008.03.014. PubMed
20. Singer AJ, Thode HC, Jr., Viccellio P, Pines JM. The association between length of emergency department boarding and mortality. Acad Emerg Med. 2011;18(12):1324-1329. doi: 10.1111/j.1553-2712.2011.01236.x. PubMed
21. White BA, Biddinger PD, Chang Y, Grabowski B, Carignan S, Brown DF. Boarding inpatients in the emergency department increases discharged patient length of stay. J Emerg Med. 2013;44(1):230-235. doi: 10.1016/j.jemermed.2012.05.007. PubMed
22. Forster AJ, Stiell I, Wells G, Lee AJ, van Walraven C. The effect of hospital occupancy on emergency department length of stay and patient disposition. Acad Emerg Med. 2003;10(2):127-133. doi: 10.1197/aemj.10.2.127. PubMed
23. Foley M, Kifaieh N, Mallon WK. Financial impact of emergency department crowding. West J Emerg Med. 2011;12(2):192-197. PubMed
24. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med. 2008;15(9):825-831. doi: 10.1111/j.1553-2712.2008.00200.x. PubMed
25. Durvasula R, Kayihan A, Del Bene S, et al. A multidisciplinary care pathway significantly increases the number of early morning discharges in a large academic medical center. Qual Manag Health Care. 2015;24:45-51. doi: 10.1097/QMH.0000000000000049. PubMed
26. Cho HJ, Desai N, Florendo A, et al. E-DIP: Early Discharge Project. A Model for Throughput and Early Discharge for 1-Day Admissions. BMJ Qual Improv Rep. 2016;5(1): pii: u210035.w4128. doi: 10.1136/bmjquality.u210035.w4128. PubMed
27. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. doi: 10.1016/j.jbi.2008.08.010. PubMed
28. Patel H, Fang MC, Mourad M, et al. Hospitalist and internal medicine leaders’ perspectives of early discharge challenges at academic medical centers. J Hosp Med. 2018;13(6):388-391. doi: 10.12788/jhm.2885. PubMed
29. Minichiello TM, Auerbach AD, Wachter RM. Caregiver perceptions of the reasons for delayed hospital discharge. Eff Clin Pract. 2001;4(6):250-255. PubMed
30. Beck MJ, Okerblom D, Kumar A, Bandyopadhyay S, Scalzi LV. Lean intervention improves patient discharge times, improves emergency department throughput and reduces congestion. Hosp Pract (1995). 2016;44(5):252-259. doi: 10.1080/21548331.2016.1254559. PubMed
31. Rajkomar A, Valencia V, Novelero M, Mourad M, Auerbach A. The association between discharge before noon and length of stay in medical and surgical patients. J Hosp Med. 2016;11(12):859-861. doi: 10.1002/jhm.2529. PubMed
32. Shine D. Discharge before noon: an urban legend. Am J Med. 2015;128(5):445-446. doi: 10.1016/j.amjmed.2014.12.011. PubMed
<--pagebreak-->33. Khanna S, Boyle J, Good N, Lind J. Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block. Emerg Med Australas. 2012;24(5):510-517. doi: 10.1111/j.1742-6723.2012.01587.x. PubMed

References

1. Wertheimer B, Jacobs RE, Bailey M, et al. Discharge before noon: an achievable hospital goal. J Hosp Med. 2014;9(4):210-214. doi: 10.1002/jhm.2154. PubMed
2. Kane M, Weinacker A, Arthofer R, et al. A multidisciplinary initiative to increase inpatient discharges before noon. J Nurs Adm. 2016;46(12):630-635. doi: 10.1097/NNA.0000000000000418. PubMed
3. Khanna S, Sier D, Boyle J, Zeitz K. Discharge timeliness and its impact on hospital crowding and emergency department flow performance. Emerg Med Australas. 2016;28(2):164-170. doi: 10.1111/1742-6723.12543. PubMed
4. Kravet SJ, Levine RB, Rubin HR, Wright SM. Discharging patients earlier in the day: a concept worth evaluating. Health Care Manag (Frederick). 2007;26:142-146. doi: 10.1097/01.HCM.0000268617.33491.60. PubMed
5. Khanna S, Boyle J, Good N, Lind J. Impact of admission and discharge peak times on hospital overcrowding. Stud Health Technol Inform. 2011;168:82-88. doi: 10.3233/978-1-60750-791-8-82. PubMed
6. McGowan JE, Truwit JD, Cipriano P, et al. Operating room efficiency and hospital capacity: factors affecting operating room use during maximum hospital census. J Am Coll Surg. 2007;204(5):865-871; discussion 71-72. doi: 10.1016/j.jamcollsurg.2007.01.052 PubMed
7. Khanna S, Boyle J, Good N, Lind J. Early discharge and its effect on ED length of stay and access block. Stud Health Technol Inform. 2012;178:92-98. doi: 10.3233/978-1-61499-078-9-92 PubMed
8. Powell ES, Khare RK, Venkatesh AK, Van Roo BD, Adams JG, Reinhardt G. The relationship between inpatient discharge timing and emergency department boarding. J Emerg Med. 2012;42(2):186-196. doi: 10.1016/j.jemermed.2010.06.028. PubMed
9. Wertheimer B, Jacobs RE, Iturrate E, Bailey M, Hochman K. Discharge before noon: Effect on throughput and sustainability. J Hosp Med. 2015;10(10):664-669. doi: 10.1002/jhm.2412. PubMed
10. Sikka R, Mehta S, Kaucky C, Kulstad EB. ED crowding is associated with an increased time to pneumonia treatment. Am J Emerg Med. 2010;28(7):809-812. doi: 10.1016/j.ajem.2009.06.023. PubMed
11. Coil CJ, Flood JD, Belyeu BM, Young P, Kaji AH, Lewis RJ. The effect of emergency department boarding on order completion. Ann Emerg Med. 2016;67:730-736 e2. doi: 10.1016/j.annemergmed.2015.09.018. PubMed
12. Gaieski DF, Agarwal AK, Mikkelsen ME, et al. The impact of ED crowding on early interventions and mortality in patients with severe sepsis. Am J Emerg Med. 2017;35:953-960. doi: 10.1016/j.ajem.2017.01.061. PubMed
13. Pines JM, Localio AR, Hollander JE, et al. The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia. Ann Emerg Med. 2007;50(5):510-516. doi: 10.1016/j.annemergmed.2007.07.021. PubMed
14. Hwang U, Richardson L, Livote E, Harris B, Spencer N, Sean Morrison R. Emergency department crowding and decreased quality of pain care. Acad Emerg Med. 2008;15:1248-1255. doi: 10.1111/j.1553-2712.2008.00267.x. PubMed
15. Mills AM, Shofer FS, Chen EH, Hollander JE, Pines JM. The association between emergency department crowding and analgesia administration in acute abdominal pain patients. Acad Emerg Med. 2009;16:603-608. doi: 10.1111/j.1553-2712.2009.00441.x. PubMed
16. Pines JM, Shofer FS, Isserman JA, Abbuhl SB, Mills AM. The effect of emergency department crowding on analgesia in patients with back pain in two hospitals. Acad Emerg Med. 2010;17(3):276-283. doi: 10.1111/j.1553-2712.2009.00676.x. PubMed
17. Kulstad EB, Sikka R, Sweis RT, Kelley KM, Rzechula KH. ED overcrowding is associated with an increased frequency of medication errors. Am J Emerg Med. 2010;28:304-309. doi: 10.1016/j.ajem.2008.12.014. PubMed
18. Richardson DB. Increase in patient mortality at 10 days associated with emergency department overcrowding. Med J Aust. 2006;184(5):213-216. PubMed
19. Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med. 2008;52(2):126-136. doi: 10.1016/j.annemergmed.2008.03.014. PubMed
20. Singer AJ, Thode HC, Jr., Viccellio P, Pines JM. The association between length of emergency department boarding and mortality. Acad Emerg Med. 2011;18(12):1324-1329. doi: 10.1111/j.1553-2712.2011.01236.x. PubMed
21. White BA, Biddinger PD, Chang Y, Grabowski B, Carignan S, Brown DF. Boarding inpatients in the emergency department increases discharged patient length of stay. J Emerg Med. 2013;44(1):230-235. doi: 10.1016/j.jemermed.2012.05.007. PubMed
22. Forster AJ, Stiell I, Wells G, Lee AJ, van Walraven C. The effect of hospital occupancy on emergency department length of stay and patient disposition. Acad Emerg Med. 2003;10(2):127-133. doi: 10.1197/aemj.10.2.127. PubMed
23. Foley M, Kifaieh N, Mallon WK. Financial impact of emergency department crowding. West J Emerg Med. 2011;12(2):192-197. PubMed
24. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med. 2008;15(9):825-831. doi: 10.1111/j.1553-2712.2008.00200.x. PubMed
25. Durvasula R, Kayihan A, Del Bene S, et al. A multidisciplinary care pathway significantly increases the number of early morning discharges in a large academic medical center. Qual Manag Health Care. 2015;24:45-51. doi: 10.1097/QMH.0000000000000049. PubMed
26. Cho HJ, Desai N, Florendo A, et al. E-DIP: Early Discharge Project. A Model for Throughput and Early Discharge for 1-Day Admissions. BMJ Qual Improv Rep. 2016;5(1): pii: u210035.w4128. doi: 10.1136/bmjquality.u210035.w4128. PubMed
27. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377-381. doi: 10.1016/j.jbi.2008.08.010. PubMed
28. Patel H, Fang MC, Mourad M, et al. Hospitalist and internal medicine leaders’ perspectives of early discharge challenges at academic medical centers. J Hosp Med. 2018;13(6):388-391. doi: 10.12788/jhm.2885. PubMed
29. Minichiello TM, Auerbach AD, Wachter RM. Caregiver perceptions of the reasons for delayed hospital discharge. Eff Clin Pract. 2001;4(6):250-255. PubMed
30. Beck MJ, Okerblom D, Kumar A, Bandyopadhyay S, Scalzi LV. Lean intervention improves patient discharge times, improves emergency department throughput and reduces congestion. Hosp Pract (1995). 2016;44(5):252-259. doi: 10.1080/21548331.2016.1254559. PubMed
31. Rajkomar A, Valencia V, Novelero M, Mourad M, Auerbach A. The association between discharge before noon and length of stay in medical and surgical patients. J Hosp Med. 2016;11(12):859-861. doi: 10.1002/jhm.2529. PubMed
32. Shine D. Discharge before noon: an urban legend. Am J Med. 2015;128(5):445-446. doi: 10.1016/j.amjmed.2014.12.011. PubMed
<--pagebreak-->33. Khanna S, Boyle J, Good N, Lind J. Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block. Emerg Med Australas. 2012;24(5):510-517. doi: 10.1111/j.1742-6723.2012.01587.x. PubMed

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Marisha Burden, MD, Division of Hospital Medicine, University of Colorado School of Medicine, 12401 East 17th Avenue, Mailstop F-782, Aurora, Colorado, 80045; Telephone: 720-848-4289; Fax: 720- 848-4293; E-mail: [email protected]
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Predictors of Clinically Significant Echocardiography Findings in Older Adults with Syncope: A Secondary Analysis

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Syncope, defined as a transient loss of consciousness and postural tone followed by complete, spontaneous return to neurological baseline, accounts for over 1 million (or approximately 1%) of all emergency department (ED) visits per year in the United States (US).12 Given the breadth of etiologies for syncope, including certain life-threatening conditions, extensive diagnostic evaluation and hospitalization for this complaint is common.3-7 The estimated costs of syncope-related hospitalizations are over $2.4 billion annually in the US.8

The 2011 American College of Cardiology Foundation appropriate use criteria for echocardiography state that syncope is an appropriate indication for transthoracic echocardiography (TTE) even when there are no other symptoms or signs of cardiovascular disease.9 This broad recommendation may be appropriate since a finding of severe valvular disease would generally merit consultation with a cardiothoracic surgeon to assess the potential for surgical intervention.10 However, routine use of echocardiogram in all syncope patients could result in increased healthcare costs, patient discomfort, and incidental findings of unclear significance, while rarely changing diagnosis or management.11,12

In an attempt to reduce potentially unnecessary TTE testing, several studies have tried to identify patients at very low risk of structural heart disease.13-17 These investigations suggest that TTE is not indicated in syncope patients with a normal ECG and a normal cardiac exam. However, this literature is limited by retrospective study design and/or small sample sizes. The 2017 American Heart Association/American College of Cardiology/Heart Rhythm Society syncope guidelines recommend TTE for a patient in whom structural heart disease is suspected, but they are not explicit about how to make this determination. 18 Thus, it is still unclear which syncope patients require TTE since a standardized approach to assessing risk of clinically significant findings on TTE has not yet been rigorously developed.

The objective of this study was to develop a risk-stratification tool to identify older adults at very low risk of having a major, clinically significant finding on rest TTE after presenting to the ED with syncope or near-syncope. Using clinical, ECG, and cardiac biomarker data, we created the ROMEO (Risk Of Major Echocardiography findings in Older adults with syncope) score to help optimize resource utilization for syncope.

 

 

METHODS

Study Design and Setting

We conducted a large, multicenter, prospective, observational cohort study of older adults who presented to an ED with syncope or near-syncope (ClinicalTrials.gov identifier: NCT01802398). The study was approved by the institutional review boards at all sites and written informed consent was obtained from all participating subjects. The study was conducted at 11 academic EDs across the US (See Appendix Table 1).

Study Population

Patient inclusion criteria for eligibility were age ≥60 years with a complaint of syncope or near-syncope. Syncope was defined as transient loss of consciousness, associated with postural loss of tone, with immediate, spontaneous, and complete recovery. Near syncope was defined as the sensation of imminent loss of consciousness. Patients were excluded if their symptoms were thought to be due to intoxication, seizure, stroke, head trauma, or hypoglycemia. Additional exclusion criteria were the need for medical intervention to restore consciousness (eg, defibrillation), new or worsening confusion, and inability to obtain informed consent from the patient or a legally authorized representative.

This analysis included only patients who received a TTE during the index visit (either in the ED, observation unit, or while admitted to the hospital). This dataset was also used for other analyses addressing questions relevant to the ED management of syncope.

Measurements

All patients underwent a standardized history, physical examination, laboratory, and 12-lead ECG testing. Trained research assistants (RA) directly queried patients about symptoms associated with the syncopal episode. Data on the patient’s past medical history, medications, and physical examination findings were collected prospectively from treating providers.

Research staff obtained blood samples for testing at a core laboratory (University of Rochester, Rochester, NY). Two assays were performed using the Roche Elecsys platform: N-terminal pro B-type natriuretic peptide (NT-proBNP) and the 5th generation high-sensitivity cardiac troponin T (hs-TnT). NT-proBNP was classified as abnormal above a cutoff of 125 pg/mL. Hs-TnT was classified as abnormal above the 99th percentile for a reference population (14 pg/mL). Although hs-TnT was not approved by the U.S. Food and Drug Administration (FDA) at the time of the study, we anticipated that this assay would receive approval and be integrated into future standard of care (FDA approval was granted in January 2017). Rest TTEs were ordered at the discretion of the treating providers.

Outcome Measures

The primary outcome for this secondary analysis was a major, clinically significant finding on TTE.13,14,16,19 These included severe aortic stenosis (<1 cm2), severe mitral stenosis, severe aortic/mitral regurgitation, reduced ejection fraction (defined either quantitatively as less than 45% or qualitatively as “severe left ventricular dysfunction”), hypertrophic cardiomyopathy with outflow tract obstruction, severe pulmonary hypertension, right ventricular dysfunction/strain, large pericardial effusion, atrial myxoma, or regional wall motion abnormalities.

All echocardiogram reports were independently reviewed by two research physicians. Discrepant reviews were resolved by the research physicians and two of the study investigators (BS, CB). Of note, all the TTEs obtained were formal echocardiographic studies, not bedside ultrasonography performed by the emergency physician.

 

 

Candidate Predictors

Potential candidate predictors were identified through a prior expert panel process.20,21 Candidate predictors included age, sex, abnormal heart sounds, exertional syncope, shortness of breath, chest pain, near-syncope, family history of sudden cardiac death, high (>180 mm Hg) or low (<90 mm Hg) systolic blood pressure, abnormal ECG, elevated hs-TnT, elevated NT-proBNP, and history of the following: hypertension, cardiac dysrhythmia, renal failure, diabetes, congestive heart failure (CHF), and coronary artery disease (CAD).

The first obtained ECG was abstracted by one of five research study physicians blinded to all clinical data. Research study physicians demonstrated high interrater reliability (kappa > 0.80) in distinguishing normal from abnormal ECGs in a training set of 50 ECGs. Abnormal ECG interpretations included nonsinus rhythms (including paced rhythms), multiple premature ventricular complexes, sinus bradycardias (≤40 bpm), ventricular hypertrophies, short PR segment intervals (<100 milliseconds [ms]), axis deviations, first degree blocks (>200 ms), complete bundle branch blocks, Brugada patterns, Wolff-Parkinson-White patterns, abnormal QRS duration (>120 ms) or abnormal QTc prolongations (>450 ms), and Q/ST/T segment abnormalities suggestive of acute or chronic ischemia.

Statistical Analysis

We calculated descriptive statistics for each predictor variable, stratified by the presence or absence of TTE findings. Chi-square and t-tests were used to test associations between categorical or continuous variables and TTE findings using a significance level of 0.05 and 2-sided hypothesis testing. To identify a robust set of predictors of the primary outcome, we used multivariate logistic regression with the LASSO (Least Absolute Shrinkage and Selection Operator) to fit a parsimonious model.22 The LASSO selects variables and shrinks the associated coefficients to avoid overfitting.23-25 We then used a bootstrap to generate confidence intervals for coefficient estimates. Cases with missing echocardiography reports were excluded from the analysis. Bootstrap results were summarized as the percentage of bootstrap iterations in which each variable’s coefficient was 1) chosen and negative, 2) shrunk to zero, or 3) chosen and positive.

We assessed different weighting schemes to generate a risk score from significant variables identified by regression modeling. These included weighting by regression coefficients rounded to the nearest integer and simple summation of the presence or absence of each variable.

Based on these results, a predictive score was developed to risk stratify patients on their probability of major, clinically significant findings on TTE. The sensitivity and specificity of a score of zero to predict findings on TTE was calculated. For confidence intervals, we used Wilson’s method for binomial confidence intervals.26 The receiver operating characteristic (ROC) curve and its associated area under the curve (AUC) were calculated, and a confidence interval for the AUC was obtained through bootstrap resampling with 2,000 iterations. As part of our sensitivity analyses, we also calculated the ROC curve and AUC after excluding the patients with a known history of CHF and significant finding on TTE. Data analyses were performed in R.27 Two sensitivity analyses were performed: 1) we used multiple imputation to impute 1,000 complete data sets and then used the same LASSO methodology as with the complete data to assess whether incorporating missing data changed the results; and 2) we simulated a conventional troponin assay by raising the positive threshold for hs-TnT to >30 pg/mL (corresponding to the limit of detection for conventional troponin).28

 

 

RESULTS

Characteristics of Study Subjects

Patient screening occurred from April 2013 to September 2016. There were 6,930 patients who met eligibility criteria, of whom 3,686 (53%) consented and enrolled in the study (See Figure 1). Of these, 995 (27%) received TTE. The mean age of patients receiving TTE was 74 years; 55% were male. Characteristics of patients obtaining and not obtaining TTE are presented in Appendix Table 2. Patients who received TTE were more likely to be older, have abnormal heart sounds, abnormal EKGs, elevated hs-TnT, elevated NT-proBNP, and have a history of CHF. Of the 995 subjects receiving TTE, 215 (21.6%) had a major, clinically significant finding.

Main Results

Univariate analysis identified 14 variables significantly associated with major findings on TTE. These included male gender, shortness of breath, abnormal heart sounds, history of renal failure, diabetes, CHF, CAD, abnormal ECG, and elevated cardiac biomarkers, among others (See Table 1). The most common major finding on TTE was regional wall motion abnormality, followed by reduced left ventricular ejection fraction (See Table 2). Of the 995 patients who received TTE, 20 (2%) were discharged directly from the ED, 444 (45%) were observed, and 531 (53%) were admitted. On average, patients who received TTE had a longer length of stay than did those that did not (3.4 days vs 1.9 days).

LASSO multivariable logistic regression produced five predictors associated with major findings on TTE: 1) history of CHF, 2) history of CAD, 3) abnormal ECG, 4) hs-TnT above 14 pg/mL, and 5) NT-proBNP above 125 pg/mL (See Table 3).



These five high-risk clinical variables retained their importance after multivariate analysis and form the ROMEO score. 
The sensitivity and specificity of a ROMEO score of zero for excluding major findings on TTE was 99.5% (95% CI: 97.4%-99.9%) and 15.4% (95% CI: 13.0%-18.1%), respectively. Patients with a ROMEO score of 0 were at very low risk of having a major finding on TTE: 0.8% (95% CI: 0.02%-4.5%; Appendix Table 3). Only one out of 121 patients with none of the ROMEO criteria was found to have a major finding on TTE (regional wall motion abnormality). Patients with a score of 1 or more were at moderate-to-high risk of having a major finding (7.3% to 55.6%).


There was a linear relationship between the ROMEO score and probability of major findings on TTE (See Appendix Figure 1). The AUC was 0.77 (95% CI = 0.72-0.79) indicating good accuracy of the combination of the five high-risk clinical variables to predict major findings on TTE (See Appendix Figure 2). After excluding the 72 patients with known CHF and significant findings on TTE, the AUC was similar: 0.73 (95% CI: 0.69-0.77). There were 139 patients with at least one missing variable (14%) (See Appendix Table 4). A multiple imputation sensitivity analysis identified the same five high-risk clinical variables in 85% of imputations.

There were 253 patients with high-sensitivity troponin levels between 15 and 30 pg/mL (inclusive). Using a higher hs-TnT threshold (>30 pg/mL) to simulate a conventional troponin assay again identified the same five high-risk variables along with shortness of breath as a potential sixth variable though with an odds ratio approaching unity (See Appendix Table 5). The ROMEO score would have missed two additional patients with major findings if the troponin cutoff were raised to 30 pg/mL from 14 pg/mL, ie, it would have identified 212/215 (98.6%) of the major findings rather than 214/215 (99.5%).

 

 

DISCUSSION

Older adults with syncope often present to the ED and undergo a variety of diagnostic tests, including TTE, and a significant proportion are admitted to the hospital.2 There is currently no standardized, evidence-based approach to guide TTE ordering for these patients. Using a large, prospective dataset of syncope patients, we sought to develop a risk-stratification tool to help clinicians identify which syncope patients would be at very low risk for clinically significant findings on TTE. We found that in the absence of these five high-risk clinical variables, the rate of significant findings on TTE in our sample was less than 1%. All five high-risk variables included in the tool remained predictive in our sensitivity analyses, speaking to the robustness of our model.

Other retrospective, and smaller prospective, studies have identified a combination of low-risk criteria including: a normal ECG alone,15 a normal physical exam and normal ECG,14,17 a negative cardiac history and normal ECG.16 Han et al. performed a chart review of 241 patients presenting to the ED with syncope and identified three risk factors for abnormal TTE findings using multiple logistic regression: age, abnormal ECG, and BNP greater than 100 pg/mL.13 While these studies’ results are generally consistent with ours, the retrospective nature and small sample size of these studies limit the generalizability of these results. Thus, using a large, multicenter prospective dataset, we derived a clinical decision instrument (the ROMEO score) to determine which older adults with syncope are at very low risk for major, clinically significant findings on TTE.

Our results add to the recent American College of Cardiology/American Heart Association/Heart Rhythm Society guidelines on the management of syncope which recommend TTE in “selected patients presenting with syncope if structural heart disease is suspected.”18 Our risk-stratification tool offers a simple, standardized approach to determine specifically when to defer TTE testing.

Our findings can guide clinicians in deciding when to obtain TTE for ED syncope patients in the following way: Older adults presenting with syncope or near-syncope to the ED who have none of the ROMEO criteria are at extremely low risk for clinically significant findings on TTE and thus need not undergo such testing solely because of the syncopal event. Patients who have only one or more high-risk clinical variables are at higher risk (7.3%-56%) of significant TTE findings. In this subset, other factors, (eg, physician gestalt, recent previous echocardiography, patient preference, availability of echocardiography) can help guide TTE ordering. Patients with a greater number of high-risk variables may benefit from a more urgent echocardiographic evaluation.

Although on average, patients undergoing TTE had a longer length of stay than those that did not, this finding does not necessarily imply that ordering a TTE was the cause of the increased length of stay. It is possible that this positive association was due to greater underlying medical complexity or acuity of illness that resulted in a greater likelihood of admission/observation, and in turn, a greater length of stay.

Prior to implementation, our results should be externally validated in other clinical settings. In the interim, this risk-stratification tool may be used by clinicians, in conjunction with clinical judgement, to help guide the appropriate use of TTE in older adults presenting with syncope.

Our study has certain limitations. As we only enrolled patients 60 years and older, our findings may not necessarily be valid in younger populations of syncope patients. However, structural heart disease is less common in younger patients and is generally more of a concern for clinicians when evaluating syncope patients in the older age range.29 In our study, 47% of eligible patients declined to participate and thus sampling bias may have occurred. TTEs were ordered at the discretion of treating providers, which was likely subject to physician, institutional, and regional variation; the prevalence of major TTE findings may be lower in the overall cohort than in patients who received TTE. Prior TTE reports were not available; therefore, we were not able to determine if these major findings were previously known. Importantly, we did not perform an internal or external validation of the ROMEO score due to time and resource constraints. Thus, this study represents a derivation of the score solely and would require external validation prior to clinical implementation. Also, to calculate the ROMEO score, both an hs-TnT and NT-proBNP level must be obtained. Thus, the cost savings of any potential reduction in TTE ordering may be partially offset by the costs of increased laboratory testing. Lastly, hs-TnT assays are not currently widely available in hospitals in the United States; earlier generation cardiac troponin assays may not be a perfect substitute for hs-TnT assays. Our sensitivity analysis using an elevated threshold for hs-TnT attempted to mitigate this limitation and resulted in similar findings.

In summary, this risk-stratification tool, using five simple criteria, could help clinicians determine which older adult syncope patients can safely forgo TTE. If validated, this tool could help optimize resource utilization, and increase the value of healthcare for patients presenting with syncope.

 

 

Acknowledgments

The authors would like to thank the research assistants at all 11 sites who enrolled patients and collected data for this study.


Disclosures

Dr. Adler has received research funding from Roche. Dr. Bastani has received research funding from Radiometer and Portola and has been a consultant for Portola. Dr. Baugh has received advisory board and speaker’s fees from Roche, research funding from Janssen and Boehringer Ingelheim, and consulting and advisory board fees from Janssen. Dr. Casterino has received funding from Astra Zeneca. Dr. Clark has received research funding from Radiometer, Ortho Clinical Trials, Janssen, Pfizer, NIH, Portola, Biocryst, Glaxo Smith Klein, Hospital Quality Foundation, and Abbott. She is a consultant for Portola, Janssen, and Hospital Quality Foundation. Dr. Diercks is a consultant for Siemens, Janssen, and Roche has received institutional research support from Novartis, Ortho Scientific, and Roche. Dr. Hollander has received research funding from Alere, Siemens, Roche, Portola, and Trinity. Dr. Hollander has also received royalties from UpToDate. Dr. Nishijima has received an honorarium from Pfizer. Dr. Storrow is a consultant for Siemens and Quidel, has received speaking fees from MCM Education, and is on the Data and Safety Monitoring Board for Trevena. Dr. Sun is a consultant for Medtronic. The other authors report no relevant conflicts of interest.


Funding

This project was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number R01 HL111033. Dr. Probst is supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K23HL132052-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Roche Diagnostics supplied the high-sensitivity troponin-T assays. The sponsoring organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, or review of the manuscript.

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References

1. Sun BC, Emond JA, Camargo CA, Jr. Characteristics and admission patterns of patients presenting with syncope to U.S. emergency departments, 1992-2000. Acad Emerg Med. 2004;11(10):1029-1034. doi: 10.1197/j.aem.2004.05.032. PubMed
2. Probst MA, Kanzaria HK, Gbedemah M, Richardson LD, Sun BC. National trends in resource utilization associated with ED visits for syncope. Am J Emerg Med. 2015;33(8):998-1001. doi: 10.1016/j.ajem.2015.04.030. PubMed
3. Kapoor WN, Karpf M, Maher Y, Miller RA, Levey GS. Syncope of unknown origin. The need for a more cost-effective approach to its diagnosis evaluation. JAMA. 1982;247(19):2687-2691. doi: 10.1001/jama.247.19.2687. PubMed
4. Pires LA, Ganji JR, Jarandila R, Steele R. Diagnostic patterns and temporal trends in the evaluation of adult patients hospitalized with syncope. Arch Intern Med. 2001;161(15):1889-1895. doi: 10.1001/archinte.161.15.1889. PubMed
5. Quinn JV, Stiell IG, McDermott DA, Sellers KL, Kohn MA, Wells GA. Derivation of the San Francisco Syncope Rule to predict patients with short-term serious outcomes. Ann Emerg Med. 2004;43(2):224-232. doi: 10.1016/S0196064403008230. PubMed
6. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 1: Value of history, physical examination, and electrocardiography. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;126(12):989-996. doi: 10.7326/0003-4819-126-12-199706150-00012. PubMed
7. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 2: Unexplained syncope. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;127(1):76-86. doi: 10.7326/0003-4819-127-1-199707010-00014. PubMed
8. Sun BC, Emond JA, Camargo CA, Jr. Direct medical costs of syncope-related hospitalizations in the United States. Am J Cardiol. 2005;95(5):668-671. doi: 10.1016/j.amjcard.2004.11.013. PubMed
9. American College of Cardiology Foundation. Appropriate Use Criteria Task F, American Society of Echocardiography, American Heart Association, et al. ACCF/ASE/AHA/ASNC/HFSA/HRS/SCAI/SCCM/SCCT/SCMR 2011 Appropriate Use Criteria for Echocardiography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance Endorsed by the American College of Chest Physicians. J Am Coll Cardiol. 2011;57(9):1126-1166. doi: 10.1016/j.echo.2010.12.008. 
10. Maganti K, Rigolin VH, Sarano ME, Bonow RO. Valvular heart disease: diagnosis and management. Mayo Clin Proc. 2010;85(5):483-500. doi: 10.4065/mcp.2009.0706. PubMed
11. Mendu ML, McAvay G, Lampert R, Stoehr J, Tinetti ME. Yield of diagnostic tests in evaluating syncopal episodes in older patients. Arch Intern Med. 2009;169(14):1299-1305. doi: 10.1001/archinternmed.2009.204. PubMed
12. Madeira CL, Craig MJ, Donohoe A, Stephens JR. Things we do for no reason: echocardiogram in unselected patients with syncope. J Hosp Med. 2017;12(12):984–988. doi: http://dx.doi.org/10.12788/jhm.2864. PubMed
13. Han SK, Yeom SR, Lee SH, et al. Transthoracic echocardiogram in syncope patients with normal initial evaluation. Am J Emerg Med. 2017;35(2):281-284. doi: 10.1016/j.ajem.2016.10.078. PubMed
14. Chang NL, Shah P, Bajaj S, Virk H, Bikkina M, Shamoon F. Diagnostic yield of echocardiography in syncope patients with normal ECG. Cardiol Res Pract. 2016;2016:1251637. doi: http://dx.doi.org/10.1155/2016/1251637. PubMed
15. Anderson KL, Limkakeng A, Damuth E, Chandra A. Cardiac evaluation for structural abnormalities may not be required in patients presenting with syncope and a normal ECG result in an observation unit setting. Ann Emerg Med. 2012;60(4):478–84.e1. doi: 10.1016/j.annemergmed.2012.04.023. PubMed
16. Sarasin FP, Junod AF, Carballo D, Slama S, Unger PF, Louis-Simonet M. Role of echocardiography in the evaluation of syncope: a prospective study. Heart. 2002;88(4):363-367. doi: 10.1136/heart.88.4.363. PubMed
17. Recchia D, Barzilai B. Echocardiography in the evaluation of patients with syncope. J Gen Intern Med. 1995;10(12):649-655. doi: 10.1007/BF02602755. PubMed
18. Shen WK, Sheldon RS, Benditt DG, et al. ACC/AHA/HRS guideline for the evaluation and management of patients With syncope: executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2017;2017(70(5)):620-663. PubMed
19. Chiu DT, Shapiro NI, Sun BC, Mottley JL, Grossman SA. Are echocardiography, telemetry, ambulatory electrocardiography monitoring, and cardiac enzymes in emergency department patients presenting with syncope useful tests? A preliminary investigation. J Emerg Med. 2014;47(1):113-118. doi: 10.1016/j.jemermed.2014.01.018. PubMed
20. Sun BC, Costantino G, Barbic F, et al. Priorities for emergency department syncope research. Ann Emerg Med. 2014;64(6):649–55.e2. doi: 10.1016/j.annemergmed.2014.04.014. PubMed
21. Sun BC, Derose SF, Liang LJ, et al. Predictors of 30-day serious events in older patients with syncope. Ann Emerg Med. 2009;54(6):769–778.e1-5. doi: 10.1016/j.annemergmed.2009.07.027. PubMed
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Syncope, defined as a transient loss of consciousness and postural tone followed by complete, spontaneous return to neurological baseline, accounts for over 1 million (or approximately 1%) of all emergency department (ED) visits per year in the United States (US).12 Given the breadth of etiologies for syncope, including certain life-threatening conditions, extensive diagnostic evaluation and hospitalization for this complaint is common.3-7 The estimated costs of syncope-related hospitalizations are over $2.4 billion annually in the US.8

The 2011 American College of Cardiology Foundation appropriate use criteria for echocardiography state that syncope is an appropriate indication for transthoracic echocardiography (TTE) even when there are no other symptoms or signs of cardiovascular disease.9 This broad recommendation may be appropriate since a finding of severe valvular disease would generally merit consultation with a cardiothoracic surgeon to assess the potential for surgical intervention.10 However, routine use of echocardiogram in all syncope patients could result in increased healthcare costs, patient discomfort, and incidental findings of unclear significance, while rarely changing diagnosis or management.11,12

In an attempt to reduce potentially unnecessary TTE testing, several studies have tried to identify patients at very low risk of structural heart disease.13-17 These investigations suggest that TTE is not indicated in syncope patients with a normal ECG and a normal cardiac exam. However, this literature is limited by retrospective study design and/or small sample sizes. The 2017 American Heart Association/American College of Cardiology/Heart Rhythm Society syncope guidelines recommend TTE for a patient in whom structural heart disease is suspected, but they are not explicit about how to make this determination. 18 Thus, it is still unclear which syncope patients require TTE since a standardized approach to assessing risk of clinically significant findings on TTE has not yet been rigorously developed.

The objective of this study was to develop a risk-stratification tool to identify older adults at very low risk of having a major, clinically significant finding on rest TTE after presenting to the ED with syncope or near-syncope. Using clinical, ECG, and cardiac biomarker data, we created the ROMEO (Risk Of Major Echocardiography findings in Older adults with syncope) score to help optimize resource utilization for syncope.

 

 

METHODS

Study Design and Setting

We conducted a large, multicenter, prospective, observational cohort study of older adults who presented to an ED with syncope or near-syncope (ClinicalTrials.gov identifier: NCT01802398). The study was approved by the institutional review boards at all sites and written informed consent was obtained from all participating subjects. The study was conducted at 11 academic EDs across the US (See Appendix Table 1).

Study Population

Patient inclusion criteria for eligibility were age ≥60 years with a complaint of syncope or near-syncope. Syncope was defined as transient loss of consciousness, associated with postural loss of tone, with immediate, spontaneous, and complete recovery. Near syncope was defined as the sensation of imminent loss of consciousness. Patients were excluded if their symptoms were thought to be due to intoxication, seizure, stroke, head trauma, or hypoglycemia. Additional exclusion criteria were the need for medical intervention to restore consciousness (eg, defibrillation), new or worsening confusion, and inability to obtain informed consent from the patient or a legally authorized representative.

This analysis included only patients who received a TTE during the index visit (either in the ED, observation unit, or while admitted to the hospital). This dataset was also used for other analyses addressing questions relevant to the ED management of syncope.

Measurements

All patients underwent a standardized history, physical examination, laboratory, and 12-lead ECG testing. Trained research assistants (RA) directly queried patients about symptoms associated with the syncopal episode. Data on the patient’s past medical history, medications, and physical examination findings were collected prospectively from treating providers.

Research staff obtained blood samples for testing at a core laboratory (University of Rochester, Rochester, NY). Two assays were performed using the Roche Elecsys platform: N-terminal pro B-type natriuretic peptide (NT-proBNP) and the 5th generation high-sensitivity cardiac troponin T (hs-TnT). NT-proBNP was classified as abnormal above a cutoff of 125 pg/mL. Hs-TnT was classified as abnormal above the 99th percentile for a reference population (14 pg/mL). Although hs-TnT was not approved by the U.S. Food and Drug Administration (FDA) at the time of the study, we anticipated that this assay would receive approval and be integrated into future standard of care (FDA approval was granted in January 2017). Rest TTEs were ordered at the discretion of the treating providers.

Outcome Measures

The primary outcome for this secondary analysis was a major, clinically significant finding on TTE.13,14,16,19 These included severe aortic stenosis (<1 cm2), severe mitral stenosis, severe aortic/mitral regurgitation, reduced ejection fraction (defined either quantitatively as less than 45% or qualitatively as “severe left ventricular dysfunction”), hypertrophic cardiomyopathy with outflow tract obstruction, severe pulmonary hypertension, right ventricular dysfunction/strain, large pericardial effusion, atrial myxoma, or regional wall motion abnormalities.

All echocardiogram reports were independently reviewed by two research physicians. Discrepant reviews were resolved by the research physicians and two of the study investigators (BS, CB). Of note, all the TTEs obtained were formal echocardiographic studies, not bedside ultrasonography performed by the emergency physician.

 

 

Candidate Predictors

Potential candidate predictors were identified through a prior expert panel process.20,21 Candidate predictors included age, sex, abnormal heart sounds, exertional syncope, shortness of breath, chest pain, near-syncope, family history of sudden cardiac death, high (>180 mm Hg) or low (<90 mm Hg) systolic blood pressure, abnormal ECG, elevated hs-TnT, elevated NT-proBNP, and history of the following: hypertension, cardiac dysrhythmia, renal failure, diabetes, congestive heart failure (CHF), and coronary artery disease (CAD).

The first obtained ECG was abstracted by one of five research study physicians blinded to all clinical data. Research study physicians demonstrated high interrater reliability (kappa > 0.80) in distinguishing normal from abnormal ECGs in a training set of 50 ECGs. Abnormal ECG interpretations included nonsinus rhythms (including paced rhythms), multiple premature ventricular complexes, sinus bradycardias (≤40 bpm), ventricular hypertrophies, short PR segment intervals (<100 milliseconds [ms]), axis deviations, first degree blocks (>200 ms), complete bundle branch blocks, Brugada patterns, Wolff-Parkinson-White patterns, abnormal QRS duration (>120 ms) or abnormal QTc prolongations (>450 ms), and Q/ST/T segment abnormalities suggestive of acute or chronic ischemia.

Statistical Analysis

We calculated descriptive statistics for each predictor variable, stratified by the presence or absence of TTE findings. Chi-square and t-tests were used to test associations between categorical or continuous variables and TTE findings using a significance level of 0.05 and 2-sided hypothesis testing. To identify a robust set of predictors of the primary outcome, we used multivariate logistic regression with the LASSO (Least Absolute Shrinkage and Selection Operator) to fit a parsimonious model.22 The LASSO selects variables and shrinks the associated coefficients to avoid overfitting.23-25 We then used a bootstrap to generate confidence intervals for coefficient estimates. Cases with missing echocardiography reports were excluded from the analysis. Bootstrap results were summarized as the percentage of bootstrap iterations in which each variable’s coefficient was 1) chosen and negative, 2) shrunk to zero, or 3) chosen and positive.

We assessed different weighting schemes to generate a risk score from significant variables identified by regression modeling. These included weighting by regression coefficients rounded to the nearest integer and simple summation of the presence or absence of each variable.

Based on these results, a predictive score was developed to risk stratify patients on their probability of major, clinically significant findings on TTE. The sensitivity and specificity of a score of zero to predict findings on TTE was calculated. For confidence intervals, we used Wilson’s method for binomial confidence intervals.26 The receiver operating characteristic (ROC) curve and its associated area under the curve (AUC) were calculated, and a confidence interval for the AUC was obtained through bootstrap resampling with 2,000 iterations. As part of our sensitivity analyses, we also calculated the ROC curve and AUC after excluding the patients with a known history of CHF and significant finding on TTE. Data analyses were performed in R.27 Two sensitivity analyses were performed: 1) we used multiple imputation to impute 1,000 complete data sets and then used the same LASSO methodology as with the complete data to assess whether incorporating missing data changed the results; and 2) we simulated a conventional troponin assay by raising the positive threshold for hs-TnT to >30 pg/mL (corresponding to the limit of detection for conventional troponin).28

 

 

RESULTS

Characteristics of Study Subjects

Patient screening occurred from April 2013 to September 2016. There were 6,930 patients who met eligibility criteria, of whom 3,686 (53%) consented and enrolled in the study (See Figure 1). Of these, 995 (27%) received TTE. The mean age of patients receiving TTE was 74 years; 55% were male. Characteristics of patients obtaining and not obtaining TTE are presented in Appendix Table 2. Patients who received TTE were more likely to be older, have abnormal heart sounds, abnormal EKGs, elevated hs-TnT, elevated NT-proBNP, and have a history of CHF. Of the 995 subjects receiving TTE, 215 (21.6%) had a major, clinically significant finding.

Main Results

Univariate analysis identified 14 variables significantly associated with major findings on TTE. These included male gender, shortness of breath, abnormal heart sounds, history of renal failure, diabetes, CHF, CAD, abnormal ECG, and elevated cardiac biomarkers, among others (See Table 1). The most common major finding on TTE was regional wall motion abnormality, followed by reduced left ventricular ejection fraction (See Table 2). Of the 995 patients who received TTE, 20 (2%) were discharged directly from the ED, 444 (45%) were observed, and 531 (53%) were admitted. On average, patients who received TTE had a longer length of stay than did those that did not (3.4 days vs 1.9 days).

LASSO multivariable logistic regression produced five predictors associated with major findings on TTE: 1) history of CHF, 2) history of CAD, 3) abnormal ECG, 4) hs-TnT above 14 pg/mL, and 5) NT-proBNP above 125 pg/mL (See Table 3).



These five high-risk clinical variables retained their importance after multivariate analysis and form the ROMEO score. 
The sensitivity and specificity of a ROMEO score of zero for excluding major findings on TTE was 99.5% (95% CI: 97.4%-99.9%) and 15.4% (95% CI: 13.0%-18.1%), respectively. Patients with a ROMEO score of 0 were at very low risk of having a major finding on TTE: 0.8% (95% CI: 0.02%-4.5%; Appendix Table 3). Only one out of 121 patients with none of the ROMEO criteria was found to have a major finding on TTE (regional wall motion abnormality). Patients with a score of 1 or more were at moderate-to-high risk of having a major finding (7.3% to 55.6%).


There was a linear relationship between the ROMEO score and probability of major findings on TTE (See Appendix Figure 1). The AUC was 0.77 (95% CI = 0.72-0.79) indicating good accuracy of the combination of the five high-risk clinical variables to predict major findings on TTE (See Appendix Figure 2). After excluding the 72 patients with known CHF and significant findings on TTE, the AUC was similar: 0.73 (95% CI: 0.69-0.77). There were 139 patients with at least one missing variable (14%) (See Appendix Table 4). A multiple imputation sensitivity analysis identified the same five high-risk clinical variables in 85% of imputations.

There were 253 patients with high-sensitivity troponin levels between 15 and 30 pg/mL (inclusive). Using a higher hs-TnT threshold (>30 pg/mL) to simulate a conventional troponin assay again identified the same five high-risk variables along with shortness of breath as a potential sixth variable though with an odds ratio approaching unity (See Appendix Table 5). The ROMEO score would have missed two additional patients with major findings if the troponin cutoff were raised to 30 pg/mL from 14 pg/mL, ie, it would have identified 212/215 (98.6%) of the major findings rather than 214/215 (99.5%).

 

 

DISCUSSION

Older adults with syncope often present to the ED and undergo a variety of diagnostic tests, including TTE, and a significant proportion are admitted to the hospital.2 There is currently no standardized, evidence-based approach to guide TTE ordering for these patients. Using a large, prospective dataset of syncope patients, we sought to develop a risk-stratification tool to help clinicians identify which syncope patients would be at very low risk for clinically significant findings on TTE. We found that in the absence of these five high-risk clinical variables, the rate of significant findings on TTE in our sample was less than 1%. All five high-risk variables included in the tool remained predictive in our sensitivity analyses, speaking to the robustness of our model.

Other retrospective, and smaller prospective, studies have identified a combination of low-risk criteria including: a normal ECG alone,15 a normal physical exam and normal ECG,14,17 a negative cardiac history and normal ECG.16 Han et al. performed a chart review of 241 patients presenting to the ED with syncope and identified three risk factors for abnormal TTE findings using multiple logistic regression: age, abnormal ECG, and BNP greater than 100 pg/mL.13 While these studies’ results are generally consistent with ours, the retrospective nature and small sample size of these studies limit the generalizability of these results. Thus, using a large, multicenter prospective dataset, we derived a clinical decision instrument (the ROMEO score) to determine which older adults with syncope are at very low risk for major, clinically significant findings on TTE.

Our results add to the recent American College of Cardiology/American Heart Association/Heart Rhythm Society guidelines on the management of syncope which recommend TTE in “selected patients presenting with syncope if structural heart disease is suspected.”18 Our risk-stratification tool offers a simple, standardized approach to determine specifically when to defer TTE testing.

Our findings can guide clinicians in deciding when to obtain TTE for ED syncope patients in the following way: Older adults presenting with syncope or near-syncope to the ED who have none of the ROMEO criteria are at extremely low risk for clinically significant findings on TTE and thus need not undergo such testing solely because of the syncopal event. Patients who have only one or more high-risk clinical variables are at higher risk (7.3%-56%) of significant TTE findings. In this subset, other factors, (eg, physician gestalt, recent previous echocardiography, patient preference, availability of echocardiography) can help guide TTE ordering. Patients with a greater number of high-risk variables may benefit from a more urgent echocardiographic evaluation.

Although on average, patients undergoing TTE had a longer length of stay than those that did not, this finding does not necessarily imply that ordering a TTE was the cause of the increased length of stay. It is possible that this positive association was due to greater underlying medical complexity or acuity of illness that resulted in a greater likelihood of admission/observation, and in turn, a greater length of stay.

Prior to implementation, our results should be externally validated in other clinical settings. In the interim, this risk-stratification tool may be used by clinicians, in conjunction with clinical judgement, to help guide the appropriate use of TTE in older adults presenting with syncope.

Our study has certain limitations. As we only enrolled patients 60 years and older, our findings may not necessarily be valid in younger populations of syncope patients. However, structural heart disease is less common in younger patients and is generally more of a concern for clinicians when evaluating syncope patients in the older age range.29 In our study, 47% of eligible patients declined to participate and thus sampling bias may have occurred. TTEs were ordered at the discretion of treating providers, which was likely subject to physician, institutional, and regional variation; the prevalence of major TTE findings may be lower in the overall cohort than in patients who received TTE. Prior TTE reports were not available; therefore, we were not able to determine if these major findings were previously known. Importantly, we did not perform an internal or external validation of the ROMEO score due to time and resource constraints. Thus, this study represents a derivation of the score solely and would require external validation prior to clinical implementation. Also, to calculate the ROMEO score, both an hs-TnT and NT-proBNP level must be obtained. Thus, the cost savings of any potential reduction in TTE ordering may be partially offset by the costs of increased laboratory testing. Lastly, hs-TnT assays are not currently widely available in hospitals in the United States; earlier generation cardiac troponin assays may not be a perfect substitute for hs-TnT assays. Our sensitivity analysis using an elevated threshold for hs-TnT attempted to mitigate this limitation and resulted in similar findings.

In summary, this risk-stratification tool, using five simple criteria, could help clinicians determine which older adult syncope patients can safely forgo TTE. If validated, this tool could help optimize resource utilization, and increase the value of healthcare for patients presenting with syncope.

 

 

Acknowledgments

The authors would like to thank the research assistants at all 11 sites who enrolled patients and collected data for this study.


Disclosures

Dr. Adler has received research funding from Roche. Dr. Bastani has received research funding from Radiometer and Portola and has been a consultant for Portola. Dr. Baugh has received advisory board and speaker’s fees from Roche, research funding from Janssen and Boehringer Ingelheim, and consulting and advisory board fees from Janssen. Dr. Casterino has received funding from Astra Zeneca. Dr. Clark has received research funding from Radiometer, Ortho Clinical Trials, Janssen, Pfizer, NIH, Portola, Biocryst, Glaxo Smith Klein, Hospital Quality Foundation, and Abbott. She is a consultant for Portola, Janssen, and Hospital Quality Foundation. Dr. Diercks is a consultant for Siemens, Janssen, and Roche has received institutional research support from Novartis, Ortho Scientific, and Roche. Dr. Hollander has received research funding from Alere, Siemens, Roche, Portola, and Trinity. Dr. Hollander has also received royalties from UpToDate. Dr. Nishijima has received an honorarium from Pfizer. Dr. Storrow is a consultant for Siemens and Quidel, has received speaking fees from MCM Education, and is on the Data and Safety Monitoring Board for Trevena. Dr. Sun is a consultant for Medtronic. The other authors report no relevant conflicts of interest.


Funding

This project was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number R01 HL111033. Dr. Probst is supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K23HL132052-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Roche Diagnostics supplied the high-sensitivity troponin-T assays. The sponsoring organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, or review of the manuscript.

Syncope, defined as a transient loss of consciousness and postural tone followed by complete, spontaneous return to neurological baseline, accounts for over 1 million (or approximately 1%) of all emergency department (ED) visits per year in the United States (US).12 Given the breadth of etiologies for syncope, including certain life-threatening conditions, extensive diagnostic evaluation and hospitalization for this complaint is common.3-7 The estimated costs of syncope-related hospitalizations are over $2.4 billion annually in the US.8

The 2011 American College of Cardiology Foundation appropriate use criteria for echocardiography state that syncope is an appropriate indication for transthoracic echocardiography (TTE) even when there are no other symptoms or signs of cardiovascular disease.9 This broad recommendation may be appropriate since a finding of severe valvular disease would generally merit consultation with a cardiothoracic surgeon to assess the potential for surgical intervention.10 However, routine use of echocardiogram in all syncope patients could result in increased healthcare costs, patient discomfort, and incidental findings of unclear significance, while rarely changing diagnosis or management.11,12

In an attempt to reduce potentially unnecessary TTE testing, several studies have tried to identify patients at very low risk of structural heart disease.13-17 These investigations suggest that TTE is not indicated in syncope patients with a normal ECG and a normal cardiac exam. However, this literature is limited by retrospective study design and/or small sample sizes. The 2017 American Heart Association/American College of Cardiology/Heart Rhythm Society syncope guidelines recommend TTE for a patient in whom structural heart disease is suspected, but they are not explicit about how to make this determination. 18 Thus, it is still unclear which syncope patients require TTE since a standardized approach to assessing risk of clinically significant findings on TTE has not yet been rigorously developed.

The objective of this study was to develop a risk-stratification tool to identify older adults at very low risk of having a major, clinically significant finding on rest TTE after presenting to the ED with syncope or near-syncope. Using clinical, ECG, and cardiac biomarker data, we created the ROMEO (Risk Of Major Echocardiography findings in Older adults with syncope) score to help optimize resource utilization for syncope.

 

 

METHODS

Study Design and Setting

We conducted a large, multicenter, prospective, observational cohort study of older adults who presented to an ED with syncope or near-syncope (ClinicalTrials.gov identifier: NCT01802398). The study was approved by the institutional review boards at all sites and written informed consent was obtained from all participating subjects. The study was conducted at 11 academic EDs across the US (See Appendix Table 1).

Study Population

Patient inclusion criteria for eligibility were age ≥60 years with a complaint of syncope or near-syncope. Syncope was defined as transient loss of consciousness, associated with postural loss of tone, with immediate, spontaneous, and complete recovery. Near syncope was defined as the sensation of imminent loss of consciousness. Patients were excluded if their symptoms were thought to be due to intoxication, seizure, stroke, head trauma, or hypoglycemia. Additional exclusion criteria were the need for medical intervention to restore consciousness (eg, defibrillation), new or worsening confusion, and inability to obtain informed consent from the patient or a legally authorized representative.

This analysis included only patients who received a TTE during the index visit (either in the ED, observation unit, or while admitted to the hospital). This dataset was also used for other analyses addressing questions relevant to the ED management of syncope.

Measurements

All patients underwent a standardized history, physical examination, laboratory, and 12-lead ECG testing. Trained research assistants (RA) directly queried patients about symptoms associated with the syncopal episode. Data on the patient’s past medical history, medications, and physical examination findings were collected prospectively from treating providers.

Research staff obtained blood samples for testing at a core laboratory (University of Rochester, Rochester, NY). Two assays were performed using the Roche Elecsys platform: N-terminal pro B-type natriuretic peptide (NT-proBNP) and the 5th generation high-sensitivity cardiac troponin T (hs-TnT). NT-proBNP was classified as abnormal above a cutoff of 125 pg/mL. Hs-TnT was classified as abnormal above the 99th percentile for a reference population (14 pg/mL). Although hs-TnT was not approved by the U.S. Food and Drug Administration (FDA) at the time of the study, we anticipated that this assay would receive approval and be integrated into future standard of care (FDA approval was granted in January 2017). Rest TTEs were ordered at the discretion of the treating providers.

Outcome Measures

The primary outcome for this secondary analysis was a major, clinically significant finding on TTE.13,14,16,19 These included severe aortic stenosis (<1 cm2), severe mitral stenosis, severe aortic/mitral regurgitation, reduced ejection fraction (defined either quantitatively as less than 45% or qualitatively as “severe left ventricular dysfunction”), hypertrophic cardiomyopathy with outflow tract obstruction, severe pulmonary hypertension, right ventricular dysfunction/strain, large pericardial effusion, atrial myxoma, or regional wall motion abnormalities.

All echocardiogram reports were independently reviewed by two research physicians. Discrepant reviews were resolved by the research physicians and two of the study investigators (BS, CB). Of note, all the TTEs obtained were formal echocardiographic studies, not bedside ultrasonography performed by the emergency physician.

 

 

Candidate Predictors

Potential candidate predictors were identified through a prior expert panel process.20,21 Candidate predictors included age, sex, abnormal heart sounds, exertional syncope, shortness of breath, chest pain, near-syncope, family history of sudden cardiac death, high (>180 mm Hg) or low (<90 mm Hg) systolic blood pressure, abnormal ECG, elevated hs-TnT, elevated NT-proBNP, and history of the following: hypertension, cardiac dysrhythmia, renal failure, diabetes, congestive heart failure (CHF), and coronary artery disease (CAD).

The first obtained ECG was abstracted by one of five research study physicians blinded to all clinical data. Research study physicians demonstrated high interrater reliability (kappa > 0.80) in distinguishing normal from abnormal ECGs in a training set of 50 ECGs. Abnormal ECG interpretations included nonsinus rhythms (including paced rhythms), multiple premature ventricular complexes, sinus bradycardias (≤40 bpm), ventricular hypertrophies, short PR segment intervals (<100 milliseconds [ms]), axis deviations, first degree blocks (>200 ms), complete bundle branch blocks, Brugada patterns, Wolff-Parkinson-White patterns, abnormal QRS duration (>120 ms) or abnormal QTc prolongations (>450 ms), and Q/ST/T segment abnormalities suggestive of acute or chronic ischemia.

Statistical Analysis

We calculated descriptive statistics for each predictor variable, stratified by the presence or absence of TTE findings. Chi-square and t-tests were used to test associations between categorical or continuous variables and TTE findings using a significance level of 0.05 and 2-sided hypothesis testing. To identify a robust set of predictors of the primary outcome, we used multivariate logistic regression with the LASSO (Least Absolute Shrinkage and Selection Operator) to fit a parsimonious model.22 The LASSO selects variables and shrinks the associated coefficients to avoid overfitting.23-25 We then used a bootstrap to generate confidence intervals for coefficient estimates. Cases with missing echocardiography reports were excluded from the analysis. Bootstrap results were summarized as the percentage of bootstrap iterations in which each variable’s coefficient was 1) chosen and negative, 2) shrunk to zero, or 3) chosen and positive.

We assessed different weighting schemes to generate a risk score from significant variables identified by regression modeling. These included weighting by regression coefficients rounded to the nearest integer and simple summation of the presence or absence of each variable.

Based on these results, a predictive score was developed to risk stratify patients on their probability of major, clinically significant findings on TTE. The sensitivity and specificity of a score of zero to predict findings on TTE was calculated. For confidence intervals, we used Wilson’s method for binomial confidence intervals.26 The receiver operating characteristic (ROC) curve and its associated area under the curve (AUC) were calculated, and a confidence interval for the AUC was obtained through bootstrap resampling with 2,000 iterations. As part of our sensitivity analyses, we also calculated the ROC curve and AUC after excluding the patients with a known history of CHF and significant finding on TTE. Data analyses were performed in R.27 Two sensitivity analyses were performed: 1) we used multiple imputation to impute 1,000 complete data sets and then used the same LASSO methodology as with the complete data to assess whether incorporating missing data changed the results; and 2) we simulated a conventional troponin assay by raising the positive threshold for hs-TnT to >30 pg/mL (corresponding to the limit of detection for conventional troponin).28

 

 

RESULTS

Characteristics of Study Subjects

Patient screening occurred from April 2013 to September 2016. There were 6,930 patients who met eligibility criteria, of whom 3,686 (53%) consented and enrolled in the study (See Figure 1). Of these, 995 (27%) received TTE. The mean age of patients receiving TTE was 74 years; 55% were male. Characteristics of patients obtaining and not obtaining TTE are presented in Appendix Table 2. Patients who received TTE were more likely to be older, have abnormal heart sounds, abnormal EKGs, elevated hs-TnT, elevated NT-proBNP, and have a history of CHF. Of the 995 subjects receiving TTE, 215 (21.6%) had a major, clinically significant finding.

Main Results

Univariate analysis identified 14 variables significantly associated with major findings on TTE. These included male gender, shortness of breath, abnormal heart sounds, history of renal failure, diabetes, CHF, CAD, abnormal ECG, and elevated cardiac biomarkers, among others (See Table 1). The most common major finding on TTE was regional wall motion abnormality, followed by reduced left ventricular ejection fraction (See Table 2). Of the 995 patients who received TTE, 20 (2%) were discharged directly from the ED, 444 (45%) were observed, and 531 (53%) were admitted. On average, patients who received TTE had a longer length of stay than did those that did not (3.4 days vs 1.9 days).

LASSO multivariable logistic regression produced five predictors associated with major findings on TTE: 1) history of CHF, 2) history of CAD, 3) abnormal ECG, 4) hs-TnT above 14 pg/mL, and 5) NT-proBNP above 125 pg/mL (See Table 3).



These five high-risk clinical variables retained their importance after multivariate analysis and form the ROMEO score. 
The sensitivity and specificity of a ROMEO score of zero for excluding major findings on TTE was 99.5% (95% CI: 97.4%-99.9%) and 15.4% (95% CI: 13.0%-18.1%), respectively. Patients with a ROMEO score of 0 were at very low risk of having a major finding on TTE: 0.8% (95% CI: 0.02%-4.5%; Appendix Table 3). Only one out of 121 patients with none of the ROMEO criteria was found to have a major finding on TTE (regional wall motion abnormality). Patients with a score of 1 or more were at moderate-to-high risk of having a major finding (7.3% to 55.6%).


There was a linear relationship between the ROMEO score and probability of major findings on TTE (See Appendix Figure 1). The AUC was 0.77 (95% CI = 0.72-0.79) indicating good accuracy of the combination of the five high-risk clinical variables to predict major findings on TTE (See Appendix Figure 2). After excluding the 72 patients with known CHF and significant findings on TTE, the AUC was similar: 0.73 (95% CI: 0.69-0.77). There were 139 patients with at least one missing variable (14%) (See Appendix Table 4). A multiple imputation sensitivity analysis identified the same five high-risk clinical variables in 85% of imputations.

There were 253 patients with high-sensitivity troponin levels between 15 and 30 pg/mL (inclusive). Using a higher hs-TnT threshold (>30 pg/mL) to simulate a conventional troponin assay again identified the same five high-risk variables along with shortness of breath as a potential sixth variable though with an odds ratio approaching unity (See Appendix Table 5). The ROMEO score would have missed two additional patients with major findings if the troponin cutoff were raised to 30 pg/mL from 14 pg/mL, ie, it would have identified 212/215 (98.6%) of the major findings rather than 214/215 (99.5%).

 

 

DISCUSSION

Older adults with syncope often present to the ED and undergo a variety of diagnostic tests, including TTE, and a significant proportion are admitted to the hospital.2 There is currently no standardized, evidence-based approach to guide TTE ordering for these patients. Using a large, prospective dataset of syncope patients, we sought to develop a risk-stratification tool to help clinicians identify which syncope patients would be at very low risk for clinically significant findings on TTE. We found that in the absence of these five high-risk clinical variables, the rate of significant findings on TTE in our sample was less than 1%. All five high-risk variables included in the tool remained predictive in our sensitivity analyses, speaking to the robustness of our model.

Other retrospective, and smaller prospective, studies have identified a combination of low-risk criteria including: a normal ECG alone,15 a normal physical exam and normal ECG,14,17 a negative cardiac history and normal ECG.16 Han et al. performed a chart review of 241 patients presenting to the ED with syncope and identified three risk factors for abnormal TTE findings using multiple logistic regression: age, abnormal ECG, and BNP greater than 100 pg/mL.13 While these studies’ results are generally consistent with ours, the retrospective nature and small sample size of these studies limit the generalizability of these results. Thus, using a large, multicenter prospective dataset, we derived a clinical decision instrument (the ROMEO score) to determine which older adults with syncope are at very low risk for major, clinically significant findings on TTE.

Our results add to the recent American College of Cardiology/American Heart Association/Heart Rhythm Society guidelines on the management of syncope which recommend TTE in “selected patients presenting with syncope if structural heart disease is suspected.”18 Our risk-stratification tool offers a simple, standardized approach to determine specifically when to defer TTE testing.

Our findings can guide clinicians in deciding when to obtain TTE for ED syncope patients in the following way: Older adults presenting with syncope or near-syncope to the ED who have none of the ROMEO criteria are at extremely low risk for clinically significant findings on TTE and thus need not undergo such testing solely because of the syncopal event. Patients who have only one or more high-risk clinical variables are at higher risk (7.3%-56%) of significant TTE findings. In this subset, other factors, (eg, physician gestalt, recent previous echocardiography, patient preference, availability of echocardiography) can help guide TTE ordering. Patients with a greater number of high-risk variables may benefit from a more urgent echocardiographic evaluation.

Although on average, patients undergoing TTE had a longer length of stay than those that did not, this finding does not necessarily imply that ordering a TTE was the cause of the increased length of stay. It is possible that this positive association was due to greater underlying medical complexity or acuity of illness that resulted in a greater likelihood of admission/observation, and in turn, a greater length of stay.

Prior to implementation, our results should be externally validated in other clinical settings. In the interim, this risk-stratification tool may be used by clinicians, in conjunction with clinical judgement, to help guide the appropriate use of TTE in older adults presenting with syncope.

Our study has certain limitations. As we only enrolled patients 60 years and older, our findings may not necessarily be valid in younger populations of syncope patients. However, structural heart disease is less common in younger patients and is generally more of a concern for clinicians when evaluating syncope patients in the older age range.29 In our study, 47% of eligible patients declined to participate and thus sampling bias may have occurred. TTEs were ordered at the discretion of treating providers, which was likely subject to physician, institutional, and regional variation; the prevalence of major TTE findings may be lower in the overall cohort than in patients who received TTE. Prior TTE reports were not available; therefore, we were not able to determine if these major findings were previously known. Importantly, we did not perform an internal or external validation of the ROMEO score due to time and resource constraints. Thus, this study represents a derivation of the score solely and would require external validation prior to clinical implementation. Also, to calculate the ROMEO score, both an hs-TnT and NT-proBNP level must be obtained. Thus, the cost savings of any potential reduction in TTE ordering may be partially offset by the costs of increased laboratory testing. Lastly, hs-TnT assays are not currently widely available in hospitals in the United States; earlier generation cardiac troponin assays may not be a perfect substitute for hs-TnT assays. Our sensitivity analysis using an elevated threshold for hs-TnT attempted to mitigate this limitation and resulted in similar findings.

In summary, this risk-stratification tool, using five simple criteria, could help clinicians determine which older adult syncope patients can safely forgo TTE. If validated, this tool could help optimize resource utilization, and increase the value of healthcare for patients presenting with syncope.

 

 

Acknowledgments

The authors would like to thank the research assistants at all 11 sites who enrolled patients and collected data for this study.


Disclosures

Dr. Adler has received research funding from Roche. Dr. Bastani has received research funding from Radiometer and Portola and has been a consultant for Portola. Dr. Baugh has received advisory board and speaker’s fees from Roche, research funding from Janssen and Boehringer Ingelheim, and consulting and advisory board fees from Janssen. Dr. Casterino has received funding from Astra Zeneca. Dr. Clark has received research funding from Radiometer, Ortho Clinical Trials, Janssen, Pfizer, NIH, Portola, Biocryst, Glaxo Smith Klein, Hospital Quality Foundation, and Abbott. She is a consultant for Portola, Janssen, and Hospital Quality Foundation. Dr. Diercks is a consultant for Siemens, Janssen, and Roche has received institutional research support from Novartis, Ortho Scientific, and Roche. Dr. Hollander has received research funding from Alere, Siemens, Roche, Portola, and Trinity. Dr. Hollander has also received royalties from UpToDate. Dr. Nishijima has received an honorarium from Pfizer. Dr. Storrow is a consultant for Siemens and Quidel, has received speaking fees from MCM Education, and is on the Data and Safety Monitoring Board for Trevena. Dr. Sun is a consultant for Medtronic. The other authors report no relevant conflicts of interest.


Funding

This project was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number R01 HL111033. Dr. Probst is supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K23HL132052-02. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Roche Diagnostics supplied the high-sensitivity troponin-T assays. The sponsoring organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, or review of the manuscript.

References

1. Sun BC, Emond JA, Camargo CA, Jr. Characteristics and admission patterns of patients presenting with syncope to U.S. emergency departments, 1992-2000. Acad Emerg Med. 2004;11(10):1029-1034. doi: 10.1197/j.aem.2004.05.032. PubMed
2. Probst MA, Kanzaria HK, Gbedemah M, Richardson LD, Sun BC. National trends in resource utilization associated with ED visits for syncope. Am J Emerg Med. 2015;33(8):998-1001. doi: 10.1016/j.ajem.2015.04.030. PubMed
3. Kapoor WN, Karpf M, Maher Y, Miller RA, Levey GS. Syncope of unknown origin. The need for a more cost-effective approach to its diagnosis evaluation. JAMA. 1982;247(19):2687-2691. doi: 10.1001/jama.247.19.2687. PubMed
4. Pires LA, Ganji JR, Jarandila R, Steele R. Diagnostic patterns and temporal trends in the evaluation of adult patients hospitalized with syncope. Arch Intern Med. 2001;161(15):1889-1895. doi: 10.1001/archinte.161.15.1889. PubMed
5. Quinn JV, Stiell IG, McDermott DA, Sellers KL, Kohn MA, Wells GA. Derivation of the San Francisco Syncope Rule to predict patients with short-term serious outcomes. Ann Emerg Med. 2004;43(2):224-232. doi: 10.1016/S0196064403008230. PubMed
6. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 1: Value of history, physical examination, and electrocardiography. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;126(12):989-996. doi: 10.7326/0003-4819-126-12-199706150-00012. PubMed
7. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 2: Unexplained syncope. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;127(1):76-86. doi: 10.7326/0003-4819-127-1-199707010-00014. PubMed
8. Sun BC, Emond JA, Camargo CA, Jr. Direct medical costs of syncope-related hospitalizations in the United States. Am J Cardiol. 2005;95(5):668-671. doi: 10.1016/j.amjcard.2004.11.013. PubMed
9. American College of Cardiology Foundation. Appropriate Use Criteria Task F, American Society of Echocardiography, American Heart Association, et al. ACCF/ASE/AHA/ASNC/HFSA/HRS/SCAI/SCCM/SCCT/SCMR 2011 Appropriate Use Criteria for Echocardiography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance Endorsed by the American College of Chest Physicians. J Am Coll Cardiol. 2011;57(9):1126-1166. doi: 10.1016/j.echo.2010.12.008. 
10. Maganti K, Rigolin VH, Sarano ME, Bonow RO. Valvular heart disease: diagnosis and management. Mayo Clin Proc. 2010;85(5):483-500. doi: 10.4065/mcp.2009.0706. PubMed
11. Mendu ML, McAvay G, Lampert R, Stoehr J, Tinetti ME. Yield of diagnostic tests in evaluating syncopal episodes in older patients. Arch Intern Med. 2009;169(14):1299-1305. doi: 10.1001/archinternmed.2009.204. PubMed
12. Madeira CL, Craig MJ, Donohoe A, Stephens JR. Things we do for no reason: echocardiogram in unselected patients with syncope. J Hosp Med. 2017;12(12):984–988. doi: http://dx.doi.org/10.12788/jhm.2864. PubMed
13. Han SK, Yeom SR, Lee SH, et al. Transthoracic echocardiogram in syncope patients with normal initial evaluation. Am J Emerg Med. 2017;35(2):281-284. doi: 10.1016/j.ajem.2016.10.078. PubMed
14. Chang NL, Shah P, Bajaj S, Virk H, Bikkina M, Shamoon F. Diagnostic yield of echocardiography in syncope patients with normal ECG. Cardiol Res Pract. 2016;2016:1251637. doi: http://dx.doi.org/10.1155/2016/1251637. PubMed
15. Anderson KL, Limkakeng A, Damuth E, Chandra A. Cardiac evaluation for structural abnormalities may not be required in patients presenting with syncope and a normal ECG result in an observation unit setting. Ann Emerg Med. 2012;60(4):478–84.e1. doi: 10.1016/j.annemergmed.2012.04.023. PubMed
16. Sarasin FP, Junod AF, Carballo D, Slama S, Unger PF, Louis-Simonet M. Role of echocardiography in the evaluation of syncope: a prospective study. Heart. 2002;88(4):363-367. doi: 10.1136/heart.88.4.363. PubMed
17. Recchia D, Barzilai B. Echocardiography in the evaluation of patients with syncope. J Gen Intern Med. 1995;10(12):649-655. doi: 10.1007/BF02602755. PubMed
18. Shen WK, Sheldon RS, Benditt DG, et al. ACC/AHA/HRS guideline for the evaluation and management of patients With syncope: executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2017;2017(70(5)):620-663. PubMed
19. Chiu DT, Shapiro NI, Sun BC, Mottley JL, Grossman SA. Are echocardiography, telemetry, ambulatory electrocardiography monitoring, and cardiac enzymes in emergency department patients presenting with syncope useful tests? A preliminary investigation. J Emerg Med. 2014;47(1):113-118. doi: 10.1016/j.jemermed.2014.01.018. PubMed
20. Sun BC, Costantino G, Barbic F, et al. Priorities for emergency department syncope research. Ann Emerg Med. 2014;64(6):649–55.e2. doi: 10.1016/j.annemergmed.2014.04.014. PubMed
21. Sun BC, Derose SF, Liang LJ, et al. Predictors of 30-day serious events in older patients with syncope. Ann Emerg Med. 2009;54(6):769–778.e1-5. doi: 10.1016/j.annemergmed.2009.07.027. PubMed
22. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc. 1996;58(1):267-288. 
23. Friedman J, Hastie T, Tibshirani R. He Elements of Statistical Learning;Vol 1. New York, NY: Springer-Verlag; 2001. PubMed
24. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33(1):1-22. doi: 10.18637/jss.v033.i01. PubMed
25. James G, Witten D, Hastie T, Tibshirani R. An Introduction to Statistical Learning;Vol 112. New York, NY: Springer-Verlag; 2013. 
26. Wilson EB. Probable inference, the law of succession, and statistical inference. J Am Stat Assoc. 1927 ;22(158):209-212. doi: 10.1080/01621459.1927.10502953. PubMed
27. R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. 
28. Chew DP, Zeitz C, Worthley M, et al. Randomized comparison of high-sensitivity troponin reporting in undifferentiated chest pain assessment. Circ Cardiovasc Qual Outcomes. 2016;9(5):542-553. doi: 10.1161/CIRCOUTCOMES.115.002488. PubMed
29. Chen RS, Bivens MJ, Grossman SA. Diagnosis and management of valvular heart disease in emergency medicine. Emerg Med Clin North Am. 2011;29(4):801–10, vii. doi: 10.1016/j.emc.2011.08.001. PubMed

References

1. Sun BC, Emond JA, Camargo CA, Jr. Characteristics and admission patterns of patients presenting with syncope to U.S. emergency departments, 1992-2000. Acad Emerg Med. 2004;11(10):1029-1034. doi: 10.1197/j.aem.2004.05.032. PubMed
2. Probst MA, Kanzaria HK, Gbedemah M, Richardson LD, Sun BC. National trends in resource utilization associated with ED visits for syncope. Am J Emerg Med. 2015;33(8):998-1001. doi: 10.1016/j.ajem.2015.04.030. PubMed
3. Kapoor WN, Karpf M, Maher Y, Miller RA, Levey GS. Syncope of unknown origin. The need for a more cost-effective approach to its diagnosis evaluation. JAMA. 1982;247(19):2687-2691. doi: 10.1001/jama.247.19.2687. PubMed
4. Pires LA, Ganji JR, Jarandila R, Steele R. Diagnostic patterns and temporal trends in the evaluation of adult patients hospitalized with syncope. Arch Intern Med. 2001;161(15):1889-1895. doi: 10.1001/archinte.161.15.1889. PubMed
5. Quinn JV, Stiell IG, McDermott DA, Sellers KL, Kohn MA, Wells GA. Derivation of the San Francisco Syncope Rule to predict patients with short-term serious outcomes. Ann Emerg Med. 2004;43(2):224-232. doi: 10.1016/S0196064403008230. PubMed
6. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 1: Value of history, physical examination, and electrocardiography. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;126(12):989-996. doi: 10.7326/0003-4819-126-12-199706150-00012. PubMed
7. Linzer M, Yang EH, Estes NA, 3rd, Wang P, Vorperian VR, Kapoor WN. Diagnosing syncope. Part 2: Unexplained syncope. Clinical Efficacy Assessment Project of the American College of Physicians. Ann Intern Med. 1997;127(1):76-86. doi: 10.7326/0003-4819-127-1-199707010-00014. PubMed
8. Sun BC, Emond JA, Camargo CA, Jr. Direct medical costs of syncope-related hospitalizations in the United States. Am J Cardiol. 2005;95(5):668-671. doi: 10.1016/j.amjcard.2004.11.013. PubMed
9. American College of Cardiology Foundation. Appropriate Use Criteria Task F, American Society of Echocardiography, American Heart Association, et al. ACCF/ASE/AHA/ASNC/HFSA/HRS/SCAI/SCCM/SCCT/SCMR 2011 Appropriate Use Criteria for Echocardiography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance Endorsed by the American College of Chest Physicians. J Am Coll Cardiol. 2011;57(9):1126-1166. doi: 10.1016/j.echo.2010.12.008. 
10. Maganti K, Rigolin VH, Sarano ME, Bonow RO. Valvular heart disease: diagnosis and management. Mayo Clin Proc. 2010;85(5):483-500. doi: 10.4065/mcp.2009.0706. PubMed
11. Mendu ML, McAvay G, Lampert R, Stoehr J, Tinetti ME. Yield of diagnostic tests in evaluating syncopal episodes in older patients. Arch Intern Med. 2009;169(14):1299-1305. doi: 10.1001/archinternmed.2009.204. PubMed
12. Madeira CL, Craig MJ, Donohoe A, Stephens JR. Things we do for no reason: echocardiogram in unselected patients with syncope. J Hosp Med. 2017;12(12):984–988. doi: http://dx.doi.org/10.12788/jhm.2864. PubMed
13. Han SK, Yeom SR, Lee SH, et al. Transthoracic echocardiogram in syncope patients with normal initial evaluation. Am J Emerg Med. 2017;35(2):281-284. doi: 10.1016/j.ajem.2016.10.078. PubMed
14. Chang NL, Shah P, Bajaj S, Virk H, Bikkina M, Shamoon F. Diagnostic yield of echocardiography in syncope patients with normal ECG. Cardiol Res Pract. 2016;2016:1251637. doi: http://dx.doi.org/10.1155/2016/1251637. PubMed
15. Anderson KL, Limkakeng A, Damuth E, Chandra A. Cardiac evaluation for structural abnormalities may not be required in patients presenting with syncope and a normal ECG result in an observation unit setting. Ann Emerg Med. 2012;60(4):478–84.e1. doi: 10.1016/j.annemergmed.2012.04.023. PubMed
16. Sarasin FP, Junod AF, Carballo D, Slama S, Unger PF, Louis-Simonet M. Role of echocardiography in the evaluation of syncope: a prospective study. Heart. 2002;88(4):363-367. doi: 10.1136/heart.88.4.363. PubMed
17. Recchia D, Barzilai B. Echocardiography in the evaluation of patients with syncope. J Gen Intern Med. 1995;10(12):649-655. doi: 10.1007/BF02602755. PubMed
18. Shen WK, Sheldon RS, Benditt DG, et al. ACC/AHA/HRS guideline for the evaluation and management of patients With syncope: executive summary: A report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2017;2017(70(5)):620-663. PubMed
19. Chiu DT, Shapiro NI, Sun BC, Mottley JL, Grossman SA. Are echocardiography, telemetry, ambulatory electrocardiography monitoring, and cardiac enzymes in emergency department patients presenting with syncope useful tests? A preliminary investigation. J Emerg Med. 2014;47(1):113-118. doi: 10.1016/j.jemermed.2014.01.018. PubMed
20. Sun BC, Costantino G, Barbic F, et al. Priorities for emergency department syncope research. Ann Emerg Med. 2014;64(6):649–55.e2. doi: 10.1016/j.annemergmed.2014.04.014. PubMed
21. Sun BC, Derose SF, Liang LJ, et al. Predictors of 30-day serious events in older patients with syncope. Ann Emerg Med. 2009;54(6):769–778.e1-5. doi: 10.1016/j.annemergmed.2009.07.027. PubMed
22. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc. 1996;58(1):267-288. 
23. Friedman J, Hastie T, Tibshirani R. He Elements of Statistical Learning;Vol 1. New York, NY: Springer-Verlag; 2001. PubMed
24. Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw. 2010;33(1):1-22. doi: 10.18637/jss.v033.i01. PubMed
25. James G, Witten D, Hastie T, Tibshirani R. An Introduction to Statistical Learning;Vol 112. New York, NY: Springer-Verlag; 2013. 
26. Wilson EB. Probable inference, the law of succession, and statistical inference. J Am Stat Assoc. 1927 ;22(158):209-212. doi: 10.1080/01621459.1927.10502953. PubMed
27. R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. 
28. Chew DP, Zeitz C, Worthley M, et al. Randomized comparison of high-sensitivity troponin reporting in undifferentiated chest pain assessment. Circ Cardiovasc Qual Outcomes. 2016;9(5):542-553. doi: 10.1161/CIRCOUTCOMES.115.002488. PubMed
29. Chen RS, Bivens MJ, Grossman SA. Diagnosis and management of valvular heart disease in emergency medicine. Emerg Med Clin North Am. 2011;29(4):801–10, vii. doi: 10.1016/j.emc.2011.08.001. PubMed

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Journal of Hospital Medicine 13(12)
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Journal of Hospital Medicine 13(12)
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823-828. Published online first September 26, 2018
Page Number
823-828. Published online first September 26, 2018
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"Marc A. Probst, MD, MS", Department of Emergency Medicine, Mount Sinai School of Medicine, 3 East 101st Street, Second Floor, Rm 218, New York, NY 10029; Telephone: 212-824-8094; Fax: 212- 426-1946; E-mail: [email protected]
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