Evaluating the effect of electroconvulsive therapy (ECT) on post-traumatic stress disorder (PTSD): A systematic review and meta-analysis of five studies
Bibliographic record
Abstract
ECT has been proposed as a potential treatment for PTSD. There is a small number of clinical studies to date, but no quantitative review of the efficacy has been conducted. We performed a systematic review and meta-analysis to evaluate the effect of ECT in reducing PTSD symptoms. We followed the PICO and the PRISMA guidelines and searched PubMed, MEDLINE (Ovid), EMBASE (Ovid), Web of Science, and the Cochrane Central Register of Controlled Trials (PROSPERO No: CRD42022356780). A random effects model meta-analysis was conducted with the pooled standard mean difference, applying Hedge's adjustment for small sample sizes. Five within-subject studies met the inclusion criteria, containing 110 patients with PTSD symptoms receiving ECT (mean age 44.13 ± 15.35; 43.4% female). ECT had a small but significant pooled effect on reducing PTSD symptoms (Hedges' g = -0.374), reducing intrusion (Hedges' g = -0.330), avoidance (Hedges' g = -0.215) and hyperarousal (Hedges' g = -0.171) symptoms. Limitations include the small number of studies and subjects and the heterogeneity of study designs. These results provide preliminary quantitative support for the use of ECT in the treatment of PTSD.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".