ABSTRACT
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.
Subject(s)
Depressive Disorder, Major , Electroconvulsive Therapy , Psychotic Disorders , Humans , Female , Male , Middle Aged , Depressive Disorder, Major/drug therapy , Psychiatric Status Rating Scales , Treatment OutcomeABSTRACT
There is increasing focus on use of resting-state functional connectivity (RSFC) analyses to subtype depression and to predict treatment response. To date, identification of RSFC patterns associated with response to electroconvulsive therapy (ECT) remain limited, and focused on interactions between dorsal prefrontal and regions of the limbic or default-mode networks. Deficits in visual processing are reported in depression, however, RSFC with or within the visual network have not been explored in recent models of depression. Here, we support prior studies showing in a sample of 18 patients with depression that connectivity between dorsal prefrontal and regions of the limbic and default-mode networks serves as a significant predictor. In addition, however, we demonstrate that including visual connectivity measures greatly increases predictive power of the RSFC algorithm (>80% accuracy of remission). These exploratory results encourage further investigation into visual dysfunction in depression, and use of RSFC algorithms incorporating the visual network in prediction of response to both ECT and transcranial magnetic stimulation (TMS), offering a new framework for the development of RSFC-guided TMS interventions in depression.
