Background: Electroconvulsive therapy (ECT) is an effective treatment for patients with severe depression. Knowledge on factors predicting therapeutic response may help to identify patients who will benefit most from the intervention. Based on the neuroplasticity hypothesis, volumes of the amygdala and hippocampus are possible candidates for predicting treatment outcome. Therefore, this prospective cohort study examines the predictive value of amygdala and hippocampal volumes for the effectiveness of ECT. Methods:Prior to ECT, 53 severely unipolar depressed patients [mean age 57 ± 14 years; 40% (n = 21) male] received structural magnetic resonance imaging (MRI) at 1.5T. Normalized amygdala and hippocampal volumes were calculated based on automatic segmentation by FreeSurfer (FS). Regression analyses were used to test if the normalized volumes could predict the response to a course of ECT based on the Montgomery-Åsberg Depression Rating Scale (MADRS) scores. Results:A larger amygdala volume independently and significantly predicted a lower post-ECT MADRS score (β = −0.347, P = 0.013).The left amygdala volume had greater predictive value for treatment outcome relative to the right amygdala volume. Hippocampal volume had no independent predictive value. Conclusion:A larger pre-treatment amygdala volume predicted more effective ECT, independent of other known predictors. Almost all patients continued their medication during the study, which might have influenced the course of treatment in ways that were not taken into account.

The current study suggests that interhemispheric coherence during ECT-induced seizures increases over the course of treatment. Furthermore, these longitudinal effects seem to be unrelated to the antidepressant efficacy of ECT. These findings contribute to the understanding of the mechanism of action of ECT.

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ObjectivesSevere postictal confusion (sPIC) is an important but poorly investigated adverse effect of electroconvulsive therapy (ECT). In this retrospective study, prevalence of sPIC and potential risk factors were explored.MethodsMedical charts of 295 ECT patients (mean ± SD age, 57 ± 15 years; male, 36%) were scrutinized for occurrence of sPIC, as well as demographic, clinical, and treatment characteristics. Patients showing sPIC were compared with patients who did not, using univariate statistics. Multivariate analyses with a split-sample validation procedure were used to assess whether predictive models could be developed using independent data sets.ResultsO 295 patients, 74 (25.1%) showed sPIC. All patients showing sPIC needed extra medication, 9% (n = 7) required physically restraints, and 5% (n = 4) had to be secluded. Univariate analyses showed several trends: patients with sPIC were more often males (P = 0.05), had more often history of cerebrovascular incident (P = 0.02), did not use concomitant selective serotonin reuptake inhibitors (P = 0.01), received higher median dosage of succinylcholine (P = 0.02), and received pretreatment with flumazenil more often (P = 0.07), but these associations did not remain significant after correction for multiple comparisons. Multiple logistic regression analysis did not result in a model that could predict sPIC in the holdout data set.ConclusionsIn this retrospective naturalistic study in 295 ECT patients, the prevalence of sPIC appeared to be 25%. Patients showing sPIC were characterized by male sex, history of cerebrovascular incident, use of higher-dose succinylcholine, and pretreatment with flumazenil. However, multivariate analysis revealed no significant model to predict sPIC in independent data.