Letters
The respondents used 61 distinct EMR systems (Q4) and came from a broad range of practice types (Q1). Nine EMRs were used by 20 or more respondents, accounted for 324 (78.8%) of all users, and users of each of these lost free time (P < .05 for all). Of these 9, the Veterans Affairs’ Computer Patient Record System (CPRS) was associated with the least free time loss (−20 minutes) (P = .04). Respondents were experienced EMR users. Most (70.6%) used all of the EMR functions listed in Q4, and 82.5% had EMRs in their practice for more than a year (Q7). Among all respondents, 89.8% reported that at least 1 data management function was slower post-EMR adoption, and 63.9% reported that note writing took longer. Surprisingly, a third (33.9%) reported that it took longer to find and review medical record data with the EMR than without, and a similar proportion, 32.2%, that it was slower to read other clinicians’ notes. The mean time loss for attending physicians was −48 minutes per clinic day (P < .001), or 4 hours per 5-day clinic week. The mean loss for trainees was −18 minutes per day, less than that of attending physicians (P < .001). For the 59.4% of all respondents who did lose time, the mean loss was −78 minutes per clinic day, or 6.5 hours per 5-day clinic week. Discussion | The loss of free time that our respondents reported was large and pervasive and could decrease access or increase costs of care. Policy makers should consider these time costs in future EMR mandates. Ambulatory practices may benefit from approaches used by high-performing practices6—the use of scribes, standing orders, talking instead of e-mail—to recapture time lost on EMR. We can only speculate as to whether better computer skills, shorter (half-day) clinic assignments with proportionately less exposure to EMR time costs, or other factors account for the trainees’ smaller per-day time loss. Clement J. McDonald, MD Fiona M. Callaghan, PhD Arlene Weissman, PhD Rebecca M. Goodwin, JD Mallika Mundkur, MD Thomson Kuhn, MS Author Affiliations: Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland (McDonald, Callaghan, Goodwin, Mundkur); American College of Physicians, Washington, DC (Weissman, Kuhn). Corresponding Author: Clement J. McDonald, MD, Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 3828, Building 38A, Room 7N707, Bethesda, MD 20894 ([email protected]). Published Online: September 8, 2014. doi:10.1001/jamainternmed.2014.4506. Author Contributions: Drs McDonald and Callaghan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: McDonald, Weissman, Goodwin, Kuhn. Acquisition, analysis, or interpretation of data: McDonald, Callaghan, Weissman, Goodwin, Mundkur. Drafting of the manuscript: McDonald, Callaghan, Weissman, Goodwin, Kuhn. Critical revision of the manuscript for important intellectual content: McDonald, Callaghan, Weissman, Goodwin, Mundkur.
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Statistical analysis: McDonald, Callaghan, Weissman. Obtained funding: McDonald. Administrative, technical, or material support: McDonald, Weissman, Goodwin, Mundkur, Kuhn. Study supervision: McDonald. Conflict of Interest Disclosures: None reported. Funding/Support: This research was supported in part by the Intramural Research Program of the National Institutes of Health and National Library of Medicine (NIH-NLM), and the American College of Physicians (ACP). Role of the Sponsor: The NIH-NLM and the ACP had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the ACP, NIH-NLM, or the US Department of Health and Human Services. 1. HIMSS13 Blog. EHR satisfaction diminishing. American EHR blog. 2013. http: //www.americanehr.com/blog/2013/03/himss13-ehr-satisfaction-diminishing/. Accessed April 18, 2014. 2. Vogel L. Cut-and-paste clinical notes confuse care, say US internists. CMAJ. 2013; 185(18):826. 3. Weir CR, Hammond KW, Embi PJ, Efthimiadis EN, Thielke SM, Hedeen AN. An exploration of the impact of computerized patient documentation on clinical collaboration. Int J Med Inform. 2011;80(8):e62-e71. 4. McDonald CJ, McDonald MH. Electronic medical records and preserving primary care physicians’ time: comment on “electronic health record-based messages to primary care providers.” Arch Intern Med. 2012;172(3):285-287. 5. Internal Medicine Insider. American College of Physicians, 2014. https: //iminsider.org/faq.php?SES=6dbcf1ab3b92904c7a1cbec86d049d14. Accessed February 19, 2014. 6. Sinsky CA, Willard-Grace R, Schutzbank AM, Sinsky TA, Margolius D, Bodenheimer T. In search of joy in practice: a report of 23 high-functioning primary care practices. Ann Fam Med. 2013;11(3):272-278.
Antidepressant Dosage and Suicidal Ideation In a recent issue of JAMA Internal Medicine, Miller and colleagues1 proposed that the risk of a suicide attempt doubles among patients 24 years or younger if the initial prescription of selective serotonin reuptake inhibitors (SSRIs) exceeds the recommended dosage. Their findings unveiled the importance of antidepressant dosage on suicidal acts but could not take into account a key risk factor, suicidal ideation (SI), and some potential clinical confounders. Indeed, the effect of type and dosage of antidepressant on the worsening of SI at treatment onset could inform clinical decisions but has been barely studied. Methods | The French National Medical Council approved the study, and written informed consent was obtained from each patient. We analyzed a subgroup of 767 adult outpatients included in a prospective naturalistic study2 after the onset of antidepressant treatment for a major depressive episode. The patient’s regular physician selected the antidepressant drug without restraints. Depression severity and SI were assessed through the Hospital Anxiety and Depression Scale and by item 9 of the self-rated Montgomery-Åsberg Depression Rating Scale, respectively. The participants completed these questionnaires at baseline and at weeks 1, 2, and 6. Patients were divided into 2 groups based on whether or not their SI scores increased during the follow-up period. Type of antidepressant (SSRI vs non-SSRI) and its dosage at JAMA Internal Medicine November 2014 Volume 174, Number 11
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Table. Sociodemographic and Clinical Characteristics of the Sample According to Whether Suicidal Ideation Worsened During the 6-Week Follow-up Perioda Nonworsening Group (n = 654)
Worsening Group (n = 113)
Odds Ratio (95% CI)
P Value
Female sex, No. (%)
419 (64.1)
63 (55.8)
0.71 (0.47-1.06)
.09
Age ≥25 y, No. (%)
617 (94.3)
106 (93.8)
0.91 (0.39-2.09)
.82
Age, mean (SD), y
44.64 (13.24)
45.36 (12.97)
1.04 (0.90-1.21) For 10-y increase
.59
Variable
Single marital status, No. (%)
276 (42.2)
48 (42.5)
1.01 (0.67-1.51)
.98
Patients with children, No. (%)
181 (27.7)
26 (23.0)
0.80 (0.50-1.28)
.34
(n = 645)
(n = 112)
≤9 y
220 (34.1)
40 (35.7)
1 [Reference]
>9 to 12 y
198 (30.7)
36 (32.1)
1.00 (0.61-1.63)
>12 y
227 (35.2)
36 (32.1)
0.87 (0.54-1.42)
Education level, No. (%)
Duration of the current MDE, mean (SD), wk Past MDEs, No. (%)
10.81 (33.57)
6.88 (5.33)
(n = 646)
(n = 112)
0
264 (40.9)
36 (32.1)
1 [Reference]
1
168 (26.0)
35 (31.3)
1.53 (0.92-2.53)
2
108 (16.7)
20 (17.9)
1.36 (0.75-2.45)
≥3 Age at first MDE, mean (SD), y Duration between current age and age at first MDE, mean (SD), y Baseline alcohol dependence, No. (%)
106 (16.4)
21 (18.8)
.04
.37
1.45 (0.81-2.60)
36.38 (13.30)
37.07 (13.78)
1.04 (0.90-1.21) For 10-y increase
.61
8.09 (10.29)
8.33 (9.75)
1.00 (0.98-1.02)
.82
17 (2.6)
7 (6.2)
2.46 (1.00-6.07)
.05
Attempted suicide during lifetime, No. (%)
173 (26.5)
36 (31.9)
1.31 (0.85-2.02)
.22
Baseline suicidal ideation MADRS score ≥2, No. (%)
538 (82.3)
89 (78.8)
0.80 (0.49-1.31)
.37
Baseline HAD anxiety score, mean (SD)
14.60 (3.36)
14.49 (3.56)
0.95 (0.71-1.28) For 5-point increase
.75
Baseline HAD depression score, mean (SD)
15.72 (3.60)
15.10 (3.63)
0.79 (0.60-1.04) For 5-point increase
.09
Baseline Beck Hopelessness Scale score, mean (SD)
10.98 (1.92)
10.78 (2.06)
0.77 (0.45-1.32) For 5-point increase
.34
treatment onset (modal vs high-dose) were compared in accord with the criteria used by Miller et al.1 Associations between SI worsening and different characteristics of patients and treatments were quantified with odds ratios (ORs) and their 95% CIs. Sociodemographic and clinical variables associated with SI worsening (at P < .15) were included in logistic regression analyses to estimate the adjusted OR for treatment type and dosage. The significance level was set at P < .05. Results | The SI scores increased for 113 patients (14.7%), and 20 patients (2.6%) attempted suicide during the follow-up period. Findings were unchanged when suicide attempters were excluded from the analysis. No significant associations were found between SI worsening and sociodemographic variables, history of depression or suicidal behavior, and baseline anxiety or hopelessness symptoms (Table). In contrast, SI worsening was associated with the use of non-SSRIs (OR, 1.63; 95% CI, 1.08-2.44), even after adjusting for sex, history of alcohol dependence, duration of the current major depressive episode, and baseline depression severity (OR, 1.66; 95% CI, 1.10-2.51). An interaction between dosage 1864
0.93 (0.87-0.99) For 2-wk increase
.82
Abbreviations: HAD, Hospital Anxiety and Depression Scale; MADRS, Montgomery-Åsberg Depression Rating Scale; MDE, major depressive episode. a
Some totals do not sum to heading totals because of missing data.
and type of treatment was observed for SI worsening (P = .04, Wald χ2 test). Therefore, the analyses were stratified into 2 groups: patients taking SSRIs and patients taking non-SSRIs (Figure). A significant association with SI worsening was found for high-dose agents at the onset of antidepressant treatment if the agent was an SSRI (OR, 2.07; 95% CI, 1.07-3.97) but not if the agent was a non-SSRI (OR, 0.83; 95% CI, 0.47-1.47). Previous failures with antidepressant medication were not associated with SI worsening. Worsening of depression, anxiety, or psychomotor activation during the follow-up period was not associated with antidepressant type or dosage. Discussion | Consistent with the results by Miller et al,1 beginning an SSRI regimen at a higher dosage than recommended (occurring in 27.8% of patients) doubled the risk of SI worsening during the first 6 weeks of treatment. This effect was independent of depression severity or suicidal risk and was not restricted to youth. In addition, as previously reported,3 a similar risk of increased SI was found when patients received nonSSRIs. Our data suggest that the use of SSRIs may reduce the risk of SI worsening relative to other antidepressants, but cau-
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Figure. Evolution of Suicidal Ideation and HAD Scores During the Follow-up Period by Type and Dosage of Antidepressant at Treatment Onset SSRI Group
Non-SSRI Group
100
30 High dose Low dose HAD total score
80 70
25
20
60 15
50 40
HAD Total Score
Patients With Suicidal Ideation, %
90
10 30 20
5
10 0
0 1 wk
Baseline
2 wk
6 wk
Baseline
1 wk
2 wk
6 wk
Time
A suicidal ideation is based on the score (>1) of item 9 of the Montgomery-Åsberg Depression Rating Scale. HAD indicates Hospital Anxiety and Depression Scale; SSRI, selective serotonin reuptake inhibitor.
tion should be exercised with the dosage. Patients 25 years or older may also need to “start low, go slow”4 when initiating a treatment for depression. Although further research is needed, these findings may help physicians choose the most appropriate type and dosage of antidepressant.
Squibb, Janssen, Lilly, Lundbeck, Otsuka, Roche, and Servier. Dr LopezCastroman reported receiving during the past 5 years honoraria for participation in scientific boards from Servier. Dr Gorwood reported receiving during the past 5 years research grants from Eli Lilly and Servier and honoraria for presentations at congresses or participation in scientific boards from AstraZeneca, BristolMyers Squibb, Janssen, Lilly, Lundbeck, Roche, and Servier. No other disclosures were reported.
Philippe Courtet, MD, PhD Jorge Lopez-Castroman, MD, PhD Isabelle Jaussent, BS, PhD Philip A. P. M. Gorwood, MD, PhD
Funding/Support: The sample was recruited with support by a research grant from Servier (Drs Courtet and Gorwood).
Author Affiliations: Centre Hospitalier Régional Universitaire de Montpellier, Institut National de la Santé et de la Récherche Médicale Unité 1061, Université Montpellier, Montpellier, France (Courtet, Lopez-Castroman, Jaussent); Fondation Fondamental, Créteil, France (Courtet, Lopez-Castroman, Jaussent); La Clinique des Maladies Mentales et de l’Encéphale, Sainte-Anne Hospital, Institut National de la Santé et de la Récherche Médicale Unité 894, Paris, France (Gorwood).
1. Miller M, Swanson SA, Azrael D, Pate V, Stürmer T. Antidepressant dose, age, and the risk of deliberate self-harm. JAMA Intern Med. 2014;174(6):899-909.
Corresponding Author: Philippe Courtet, MD, PhD, Centre Hospitalier Régional Universitaire de Montpellier, Institut National de la Santé et de la Récherche Médicale Unité 1061, Université Montpellier, Pavillon 42, 39 Ave Charles Flahault, Boite Postale 34493, 34093 Montpellier CEDEX 5, France (philippe [email protected]). Published Online: September 22, 2014. doi:10.1001/jamainternmed.2014.4509. Author Contributions: Dr Jaussent had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Courtet, Jaussent, Gorwood. Acquisition, analysis, or interpretation of data: Courtet, Lopez-Castroman, Jaussent. Drafting of the manuscript: Courtet, Lopez-Castroman, Jaussent. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Jaussent. Obtained funding: Gorwood. Administrative, technical, or material support: Lopez-Castroman. Study supervision: Courtet, Gorwood. Conflict of Interest Disclosures: Dr Courtet reported receiving during the past 5 years research grants from Servier and honoraria for presentations at congresses or participation in scientific boards from AstraZeneca, Bristol-Myers jamainternalmedicine.com
Role of Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
2. Courtet PH, Jaussent I, Lopez-Castroman J, Gorwood PH. Poor response to antidepressants predicts new suicidal ideas and behavior in depressed outpatients. Eur Neuropsychopharmacol. In press. doi:10.1016/j.euroneuro.2014 .07.007. 3. Perroud N, Uher R, Marusic A, et al. Suicidal ideation during treatment of depression with escitalopram and nortriptyline in Genome-Based Therapeutic Drugs for Depression (GENDEP): a clinical trial. BMC Med. 2009;7:60. doi:10 .1186/1741-7015-7-60. 4. Brent DA, Gibbons R. Initial dose of antidepressant and suicidal behavior in youth: start low, go slow. JAMA Intern Med. 2014;174(6):909-911.
Inpatient Attire: An Opportunity to Improve the Patient Experience A recent commentary in JAMA1(p2169) suggested that patients should be encouraged to wear their own clothing so they might “maintain their self-esteem and orientation and also remind their care professionals to recognize them as people.” Other articles suggest that traditional patient gowns are associated with a loss of dignity, the reinforcement of the “patient role,” and the assumption of a low-status position in the hospital.2,3 Far more has been written on the attire of health care practitioners than that of patients. JAMA Internal Medicine November 2014 Volume 174, Number 11
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The respondents used 61 distinct EMR systems (Q4) and came from a broad range of practice types (Q1). Nine EMRs were used by 20 or more respondents, accounted for 324 (78.8%) of all users, and users of each of these lost free time (P < .05 for all). Of these 9, the Veterans Affairs’ Computer Patient Record System (CPRS) was associated with the least free time loss (−20 minutes) (P = .04). Respondents were experienced EMR users. Most (70.6%) used all of the EMR functions listed in Q4, and 82.5% had EMRs in their practice for more than a year (Q7). Among all respondents, 89.8% reported that at least 1 data management function was slower post-EMR adoption, and 63.9% reported that note writing took longer. Surprisingly, a third (33.9%) reported that it took longer to find and review medical record data with the EMR than without, and a similar proportion, 32.2%, that it was slower to read other clinicians’ notes. The mean time loss for attending physicians was −48 minutes per clinic day (P < .001), or 4 hours per 5-day clinic week. The mean loss for trainees was −18 minutes per day, less than that of attending physicians (P < .001). For the 59.4% of all respondents who did lose time, the mean loss was −78 minutes per clinic day, or 6.5 hours per 5-day clinic week. Discussion | The loss of free time that our respondents reported was large and pervasive and could decrease access or increase costs of care. Policy makers should consider these time costs in future EMR mandates. Ambulatory practices may benefit from approaches used by high-performing practices6—the use of scribes, standing orders, talking instead of e-mail—to recapture time lost on EMR. We can only speculate as to whether better computer skills, shorter (half-day) clinic assignments with proportionately less exposure to EMR time costs, or other factors account for the trainees’ smaller per-day time loss. Clement J. McDonald, MD Fiona M. Callaghan, PhD Arlene Weissman, PhD Rebecca M. Goodwin, JD Mallika Mundkur, MD Thomson Kuhn, MS Author Affiliations: Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland (McDonald, Callaghan, Goodwin, Mundkur); American College of Physicians, Washington, DC (Weissman, Kuhn). Corresponding Author: Clement J. McDonald, MD, Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 3828, Building 38A, Room 7N707, Bethesda, MD 20894 ([email protected]). Published Online: September 8, 2014. doi:10.1001/jamainternmed.2014.4506. Author Contributions: Drs McDonald and Callaghan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: McDonald, Weissman, Goodwin, Kuhn. Acquisition, analysis, or interpretation of data: McDonald, Callaghan, Weissman, Goodwin, Mundkur. Drafting of the manuscript: McDonald, Callaghan, Weissman, Goodwin, Kuhn. Critical revision of the manuscript for important intellectual content: McDonald, Callaghan, Weissman, Goodwin, Mundkur.
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Statistical analysis: McDonald, Callaghan, Weissman. Obtained funding: McDonald. Administrative, technical, or material support: McDonald, Weissman, Goodwin, Mundkur, Kuhn. Study supervision: McDonald. Conflict of Interest Disclosures: None reported. Funding/Support: This research was supported in part by the Intramural Research Program of the National Institutes of Health and National Library of Medicine (NIH-NLM), and the American College of Physicians (ACP). Role of the Sponsor: The NIH-NLM and the ACP had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the ACP, NIH-NLM, or the US Department of Health and Human Services. 1. HIMSS13 Blog. EHR satisfaction diminishing. American EHR blog. 2013. http: //www.americanehr.com/blog/2013/03/himss13-ehr-satisfaction-diminishing/. Accessed April 18, 2014. 2. Vogel L. Cut-and-paste clinical notes confuse care, say US internists. CMAJ. 2013; 185(18):826. 3. Weir CR, Hammond KW, Embi PJ, Efthimiadis EN, Thielke SM, Hedeen AN. An exploration of the impact of computerized patient documentation on clinical collaboration. Int J Med Inform. 2011;80(8):e62-e71. 4. McDonald CJ, McDonald MH. Electronic medical records and preserving primary care physicians’ time: comment on “electronic health record-based messages to primary care providers.” Arch Intern Med. 2012;172(3):285-287. 5. Internal Medicine Insider. American College of Physicians, 2014. https: //iminsider.org/faq.php?SES=6dbcf1ab3b92904c7a1cbec86d049d14. Accessed February 19, 2014. 6. Sinsky CA, Willard-Grace R, Schutzbank AM, Sinsky TA, Margolius D, Bodenheimer T. In search of joy in practice: a report of 23 high-functioning primary care practices. Ann Fam Med. 2013;11(3):272-278.
Antidepressant Dosage and Suicidal Ideation In a recent issue of JAMA Internal Medicine, Miller and colleagues1 proposed that the risk of a suicide attempt doubles among patients 24 years or younger if the initial prescription of selective serotonin reuptake inhibitors (SSRIs) exceeds the recommended dosage. Their findings unveiled the importance of antidepressant dosage on suicidal acts but could not take into account a key risk factor, suicidal ideation (SI), and some potential clinical confounders. Indeed, the effect of type and dosage of antidepressant on the worsening of SI at treatment onset could inform clinical decisions but has been barely studied. Methods | The French National Medical Council approved the study, and written informed consent was obtained from each patient. We analyzed a subgroup of 767 adult outpatients included in a prospective naturalistic study2 after the onset of antidepressant treatment for a major depressive episode. The patient’s regular physician selected the antidepressant drug without restraints. Depression severity and SI were assessed through the Hospital Anxiety and Depression Scale and by item 9 of the self-rated Montgomery-Åsberg Depression Rating Scale, respectively. The participants completed these questionnaires at baseline and at weeks 1, 2, and 6. Patients were divided into 2 groups based on whether or not their SI scores increased during the follow-up period. Type of antidepressant (SSRI vs non-SSRI) and its dosage at JAMA Internal Medicine November 2014 Volume 174, Number 11
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Table. Sociodemographic and Clinical Characteristics of the Sample According to Whether Suicidal Ideation Worsened During the 6-Week Follow-up Perioda Nonworsening Group (n = 654)
Worsening Group (n = 113)
Odds Ratio (95% CI)
P Value
Female sex, No. (%)
419 (64.1)
63 (55.8)
0.71 (0.47-1.06)
.09
Age ≥25 y, No. (%)
617 (94.3)
106 (93.8)
0.91 (0.39-2.09)
.82
Age, mean (SD), y
44.64 (13.24)
45.36 (12.97)
1.04 (0.90-1.21) For 10-y increase
.59
Variable
Single marital status, No. (%)
276 (42.2)
48 (42.5)
1.01 (0.67-1.51)
.98
Patients with children, No. (%)
181 (27.7)
26 (23.0)
0.80 (0.50-1.28)
.34
(n = 645)
(n = 112)
≤9 y
220 (34.1)
40 (35.7)
1 [Reference]
>9 to 12 y
198 (30.7)
36 (32.1)
1.00 (0.61-1.63)
>12 y
227 (35.2)
36 (32.1)
0.87 (0.54-1.42)
Education level, No. (%)
Duration of the current MDE, mean (SD), wk Past MDEs, No. (%)
10.81 (33.57)
6.88 (5.33)
(n = 646)
(n = 112)
0
264 (40.9)
36 (32.1)
1 [Reference]
1
168 (26.0)
35 (31.3)
1.53 (0.92-2.53)
2
108 (16.7)
20 (17.9)
1.36 (0.75-2.45)
≥3 Age at first MDE, mean (SD), y Duration between current age and age at first MDE, mean (SD), y Baseline alcohol dependence, No. (%)
106 (16.4)
21 (18.8)
.04
.37
1.45 (0.81-2.60)
36.38 (13.30)
37.07 (13.78)
1.04 (0.90-1.21) For 10-y increase
.61
8.09 (10.29)
8.33 (9.75)
1.00 (0.98-1.02)
.82
17 (2.6)
7 (6.2)
2.46 (1.00-6.07)
.05
Attempted suicide during lifetime, No. (%)
173 (26.5)
36 (31.9)
1.31 (0.85-2.02)
.22
Baseline suicidal ideation MADRS score ≥2, No. (%)
538 (82.3)
89 (78.8)
0.80 (0.49-1.31)
.37
Baseline HAD anxiety score, mean (SD)
14.60 (3.36)
14.49 (3.56)
0.95 (0.71-1.28) For 5-point increase
.75
Baseline HAD depression score, mean (SD)
15.72 (3.60)
15.10 (3.63)
0.79 (0.60-1.04) For 5-point increase
.09
Baseline Beck Hopelessness Scale score, mean (SD)
10.98 (1.92)
10.78 (2.06)
0.77 (0.45-1.32) For 5-point increase
.34
treatment onset (modal vs high-dose) were compared in accord with the criteria used by Miller et al.1 Associations between SI worsening and different characteristics of patients and treatments were quantified with odds ratios (ORs) and their 95% CIs. Sociodemographic and clinical variables associated with SI worsening (at P < .15) were included in logistic regression analyses to estimate the adjusted OR for treatment type and dosage. The significance level was set at P < .05. Results | The SI scores increased for 113 patients (14.7%), and 20 patients (2.6%) attempted suicide during the follow-up period. Findings were unchanged when suicide attempters were excluded from the analysis. No significant associations were found between SI worsening and sociodemographic variables, history of depression or suicidal behavior, and baseline anxiety or hopelessness symptoms (Table). In contrast, SI worsening was associated with the use of non-SSRIs (OR, 1.63; 95% CI, 1.08-2.44), even after adjusting for sex, history of alcohol dependence, duration of the current major depressive episode, and baseline depression severity (OR, 1.66; 95% CI, 1.10-2.51). An interaction between dosage 1864
0.93 (0.87-0.99) For 2-wk increase
.82
Abbreviations: HAD, Hospital Anxiety and Depression Scale; MADRS, Montgomery-Åsberg Depression Rating Scale; MDE, major depressive episode. a
Some totals do not sum to heading totals because of missing data.
and type of treatment was observed for SI worsening (P = .04, Wald χ2 test). Therefore, the analyses were stratified into 2 groups: patients taking SSRIs and patients taking non-SSRIs (Figure). A significant association with SI worsening was found for high-dose agents at the onset of antidepressant treatment if the agent was an SSRI (OR, 2.07; 95% CI, 1.07-3.97) but not if the agent was a non-SSRI (OR, 0.83; 95% CI, 0.47-1.47). Previous failures with antidepressant medication were not associated with SI worsening. Worsening of depression, anxiety, or psychomotor activation during the follow-up period was not associated with antidepressant type or dosage. Discussion | Consistent with the results by Miller et al,1 beginning an SSRI regimen at a higher dosage than recommended (occurring in 27.8% of patients) doubled the risk of SI worsening during the first 6 weeks of treatment. This effect was independent of depression severity or suicidal risk and was not restricted to youth. In addition, as previously reported,3 a similar risk of increased SI was found when patients received nonSSRIs. Our data suggest that the use of SSRIs may reduce the risk of SI worsening relative to other antidepressants, but cau-
JAMA Internal Medicine November 2014 Volume 174, Number 11
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Figure. Evolution of Suicidal Ideation and HAD Scores During the Follow-up Period by Type and Dosage of Antidepressant at Treatment Onset SSRI Group
Non-SSRI Group
100
30 High dose Low dose HAD total score
80 70
25
20
60 15
50 40
HAD Total Score
Patients With Suicidal Ideation, %
90
10 30 20
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A suicidal ideation is based on the score (>1) of item 9 of the Montgomery-Åsberg Depression Rating Scale. HAD indicates Hospital Anxiety and Depression Scale; SSRI, selective serotonin reuptake inhibitor.
tion should be exercised with the dosage. Patients 25 years or older may also need to “start low, go slow”4 when initiating a treatment for depression. Although further research is needed, these findings may help physicians choose the most appropriate type and dosage of antidepressant.
Squibb, Janssen, Lilly, Lundbeck, Otsuka, Roche, and Servier. Dr LopezCastroman reported receiving during the past 5 years honoraria for participation in scientific boards from Servier. Dr Gorwood reported receiving during the past 5 years research grants from Eli Lilly and Servier and honoraria for presentations at congresses or participation in scientific boards from AstraZeneca, BristolMyers Squibb, Janssen, Lilly, Lundbeck, Roche, and Servier. No other disclosures were reported.
Philippe Courtet, MD, PhD Jorge Lopez-Castroman, MD, PhD Isabelle Jaussent, BS, PhD Philip A. P. M. Gorwood, MD, PhD
Funding/Support: The sample was recruited with support by a research grant from Servier (Drs Courtet and Gorwood).
Author Affiliations: Centre Hospitalier Régional Universitaire de Montpellier, Institut National de la Santé et de la Récherche Médicale Unité 1061, Université Montpellier, Montpellier, France (Courtet, Lopez-Castroman, Jaussent); Fondation Fondamental, Créteil, France (Courtet, Lopez-Castroman, Jaussent); La Clinique des Maladies Mentales et de l’Encéphale, Sainte-Anne Hospital, Institut National de la Santé et de la Récherche Médicale Unité 894, Paris, France (Gorwood).
1. Miller M, Swanson SA, Azrael D, Pate V, Stürmer T. Antidepressant dose, age, and the risk of deliberate self-harm. JAMA Intern Med. 2014;174(6):899-909.
Corresponding Author: Philippe Courtet, MD, PhD, Centre Hospitalier Régional Universitaire de Montpellier, Institut National de la Santé et de la Récherche Médicale Unité 1061, Université Montpellier, Pavillon 42, 39 Ave Charles Flahault, Boite Postale 34493, 34093 Montpellier CEDEX 5, France (philippe [email protected]). Published Online: September 22, 2014. doi:10.1001/jamainternmed.2014.4509. Author Contributions: Dr Jaussent had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Courtet, Jaussent, Gorwood. Acquisition, analysis, or interpretation of data: Courtet, Lopez-Castroman, Jaussent. Drafting of the manuscript: Courtet, Lopez-Castroman, Jaussent. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Jaussent. Obtained funding: Gorwood. Administrative, technical, or material support: Lopez-Castroman. Study supervision: Courtet, Gorwood. Conflict of Interest Disclosures: Dr Courtet reported receiving during the past 5 years research grants from Servier and honoraria for presentations at congresses or participation in scientific boards from AstraZeneca, Bristol-Myers jamainternalmedicine.com
Role of Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
2. Courtet PH, Jaussent I, Lopez-Castroman J, Gorwood PH. Poor response to antidepressants predicts new suicidal ideas and behavior in depressed outpatients. Eur Neuropsychopharmacol. In press. doi:10.1016/j.euroneuro.2014 .07.007. 3. Perroud N, Uher R, Marusic A, et al. Suicidal ideation during treatment of depression with escitalopram and nortriptyline in Genome-Based Therapeutic Drugs for Depression (GENDEP): a clinical trial. BMC Med. 2009;7:60. doi:10 .1186/1741-7015-7-60. 4. Brent DA, Gibbons R. Initial dose of antidepressant and suicidal behavior in youth: start low, go slow. JAMA Intern Med. 2014;174(6):909-911.
Inpatient Attire: An Opportunity to Improve the Patient Experience A recent commentary in JAMA1(p2169) suggested that patients should be encouraged to wear their own clothing so they might “maintain their self-esteem and orientation and also remind their care professionals to recognize them as people.” Other articles suggest that traditional patient gowns are associated with a loss of dignity, the reinforcement of the “patient role,” and the assumption of a low-status position in the hospital.2,3 Far more has been written on the attire of health care practitioners than that of patients. JAMA Internal Medicine November 2014 Volume 174, Number 11
Copyright 2014 American Medical Association. All rights reserved.
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