4.7 Article

Sex-specifics of ECT outcome

Journal

JOURNAL OF AFFECTIVE DISORDERS
Volume 326, Issue -, Pages 243-248

Publisher

ELSEVIER
DOI: 10.1016/j.jad.2022.12.144

Keywords

Electroconvulsive therapy; ECT; Sex; Sex-specific; Major depressive disorder; Phenotype; Predictor

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Electroconvulsive therapy (ECT) is equally effective for both men and women with severe major depressive disorder (MDD). However, shorter duration of index episode may serve as a specific predictor for remission in women.
Objective: Electroconvulsive therapy (ECT) is the most effective treatment for patients with severe major depressive disorder (MDD). Given the known sex differences in MDD, improved knowledge may provide more sex-specific recommendations in clinical guidelines and improve outcome. In the present study we examine sex differences in ECT outcome and its predictors. Methods: Clinical data from 20 independent sites participating in the Global ECT-MRI Research Collaboration (GEMRIC) were obtained for analysis, totaling 500 patients with MDD (58.6 % women) with a mean age of 54.8 years. Severity of depression before and after ECT was assessed with validated depression scales. Remission was defined as a HAM-D score of 7 points or below after ECT. Variables associated with remission were selected based on literature (i.e. depression severity at baseline, age, duration of index episode, and presence of psychotic symptoms). Results: Remission rates of ECT were independent of sex, 48.0 % in women and 45.7 % in men (X2(1) = 0.2, p = 0.70). In the logistic regression analyses, a shorter index duration was identified as a sex-specific predictor for ECT outcome in women (X2(1) = 7.05, p = 0.01). The corresponding predictive margins did show overlapping confidence intervals for men and women. Conclusion: The evidence provided by our study suggests that ECT as a biological treatment for MDD is equally effective in women and men. A shorter duration of index episode was an additional sex-specific predictor for remission in women. Future research should establish whether the confidence intervals for the corresponding predictive margins are overlapping, as we find, or not.

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