Efficacy of Continuation/Maintenance Electroconvulsive Therapy for the Prevention of Recurrence of a Major Depressive Episode in Adults With Unipolar Depression
Bibliographic record
Abstract
OBJECTIVE: Divergent opinion surrounds the use of continuation/maintenance electroconvulsive therapy (c/mECT) as a recurrence prevention strategy in depression because of limited data on efficacy and adverse effects. In an effort to synthesize what is known about its efficacy, a systematic review of controlled studies reporting efficacy of c/mECT for the prevention of relapse or recurrence of a depressive episode in adults with unipolar major depression was conducted. METHODS: Eleven electronic databases were searched with a 3-stage screening process conducted by the author with an independent review. Quality assessments and data extractions were performed on selected studies using preselected tools. RESULTS: Six studies met the inclusion criteria; these are as follows: 3 randomized controlled trials, 1 small nonrandomized controlled trial, and 2 retrospective chart reviews. All participants had undergone an index course of electroconvulsive therapy with positive effects before receiving c/mECT or control/comparison interventions. One randomized controlled trial and retrospective chart review showed no significant difference between c/mECT and control/comparison interventions; the remaining 4 studies showed a significantly superior effect of c/mECT for the prevention of recurrence of depression. Monotherapy of c/mECT was less efficacious than c/mECT in combination with antidepressant medication, as was c/mECT delivered on a schedule, which was unresponsive to early signs of recurrence. CONCLUSIONS: This review suggests that c/mECT is efficacious for the prevention of relapse/recurrence of major depression and that efficacy is increased when c/mECT is provided in combination with antidepressant medication and at flexible treatment intervals, responsive to early signs of recurrence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".