Aazaz U Haq 1,2 , Adam F Sitzmann , Mona L Goldman , Daniel F Maixner , Brian J Mickey Show Affiliations »
Abstract
OBJECTIVE: Roughly one-third of individuals with depression do not respond to electroconvulsive therapy (ECT). Reliable predictors of ECT response would be useful for patient selection, but have not been demonstrated definitively. We used meta-analysis to measure effect sizes for a series of clinical predictors of ECT response in depression. DATA SOURCES: PubMed was searched systematically to identify studies published after 1980 that tested at least 1 clinical predictor of response to ECT. STUDY SELECTION: Of 51 studies identified, 32 were compatible with meta-analysis. DATA EXTRACTION: The weighted mean odds ratio (OR) or standardized mean difference (SMD) was computed for each of 10 clinical predictors, based on dichotomous outcomes (responder vs nonresponder). Statistical analyses examined robustness, bias, and heterogeneity. RESULTS: Shorter depressive episode duration predicted higher ECT response rate (SMD = -0.37, 7 studies, 702 subjects, P = 4 × 10(-6)). History of medication failure in the current episode was also a robust predictor: response rates were 58% and 70%, respectively, for those with and without medication failure (OR = 0.56, 11 studies, 1,175 subjects, P = 1 × 10(-5)). Greater age and psychotic features were weakly associated with higher ECT response rates, but heterogeneity was notable. Bipolar diagnosis, sex, age at onset, and number of previous episodes were not significant predictors. Analyses of symptom severity and melancholic features were inconclusive due to study heterogeneity. CONCLUSIONS: Longer depressive episodes and medication failure at baseline are robust predictors of poor response to ECT, with effect sizes that are modest but clinically relevant. Patient characteristics used traditionally such as age, psychosis, and melancholic features are less likely to be clinically useful. More robust clinical and biological predictors are needed for management of depressed patients considering ECT. © Copyright 2015 Physicians Postgraduate Press, Inc.
OBJECTIVE: Roughly one-third of individuals with depression do not respond to electroconvulsive therapy (ECT). Reliable predictors of ECT response would be useful for patient selection, but have not been demonstrated definitively. We used meta-analysis to measure effect sizes for a series of clinical predictors of ECT response in depression . DATA SOURCES: PubMed was searched systematically to identify studies published after 1980 that tested at least 1 clinical predictor of response to ECT. STUDY SELECTION: Of 51 studies identified, 32 were compatible with meta-analysis. DATA EXTRACTION: The weighted mean odds ratio (OR) or standardized mean difference (SMD ) was computed for each of 10 clinical predictors, based on dichotomous outcomes (responder vs nonresponder). Statistical analyses examined robustness, bias, and heterogeneity. RESULTS: Shorter depressive episode duration predicted higher ECT response rate (SMD = -0.37, 7 studies, 702 subjects, P = 4 × 10(-6)). History of medication failure in the current episode was also a robust predictor: response rates were 58% and 70%, respectively, for those with and without medication failure (OR = 0.56, 11 studies, 1,175 subjects, P = 1 × 10(-5)). Greater age and psychotic features were weakly associated with higher ECT response rates, but heterogeneity was notable. Bipolar diagnosis, sex, age at onset, and number of previous episodes were not significant predictors. Analyses of symptom severity and melancholic features were inconclusive due to study heterogeneity. CONCLUSIONS: Longer depressive episodes and medication failure at baseline are robust predictors of poor response to ECT, with effect sizes that are modest but clinically relevant. Patient characteristics used traditionally such as age, psychosis , and melancholic features are less likely to be clinically useful. More robust clinical and biological predictors are needed for management of depressed patients considering ECT. © Copyright 2015 Physicians Postgraduate Press, Inc.
Entities: Disease
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Year: 2015
PMID： 26528644 DOI： 10.4088/JCP.14r09528
Source DB: PubMed Journal: J Clin Psychiatry ISSN： 0160-6689 Impact factor: 4.384