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Effective strategies to prolong remission after electroconvulsive therapy (ECT) are urgently needed. Fixed schedules for continuation ECT (C-ECT) cannot adapt to early signs of impending relapse. Symptom-Titrated, Algorithm-Based Longitudinal ECT (STABLE) is proposed as a novel patient-focused approach to individualize the ECT schedule. In STABLE, the ECT schedule adapts to symptom fluctuations to prevent overtreatment of those who do not need it and to recapture response in those who might have otherwise relapsed with a rigid dosing schedule. Here we back-test STABLE to optimize the algorithm for subsequent testing in a prospective trial.

Toward Individualized Post-Electroconvulsive Therapy Care