Prediction of electroconvulsive therapy outcome: A network analysis approach.

ABSTRACT:

Objective

While electroconvulsive therapy (ECT) for the treatment of major depressive disorder is effective, individual response is variable and difficult to predict. These difficulties may in part result from heterogeneity at the symptom level. We aim to predict remission using baseline depression symptoms, taking the associations among symptoms into account, by using a network analysis approach.

Method

We combined individual patient data from two randomized controlled trials (total N = 161) and estimated a Mixed Graphical Model to estimate which baseline depression symptoms (corresponding to HRSD-17 items) uniquely predicted remission (defined as either HRSD≤7 or MADRS<10). We included study as moderator to evaluate study heterogeneity. For symptoms directly predictive of

SUBMITTER: Blanken TF 

PROVIDER: S-EPMC11884910 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature