Magnetic Seizure Therapy in Refractory Psychiatric Disorders: A Systematic Review and Meta-Analysis: La thérapie par convulsions magnétiques pour la prise en charge des troubles psychiatriques réfractaires : revue systématique et méta-analyse
Bibliographic record
Abstract
Objective: To qualitatively and quantitatively synthesize the literature on the efficacy and safety of magnetic seizure therapy (MST) in psychiatric disorders. Methods: A literature search was conducted of the OVID Medline, OVID EMBASE, PsychINFO, CINAHL, Web of Science and Cochrane databases from inception to 14 January 2024, using subject headings and key words for “magnetic seizure therapy.” Randomized controlled trials (RCTs), post-hoc analyses of RCTs, open-label trials, or case series investigating MST in adults with a verified psychiatric diagnosis and reporting on two possible primary outcomes (1) psychiatric symptom reduction (as measured by validated rating scale) or (2) neurocognitive outcomes (as measured by standardized testing), were included. Abstracts, individual case reports, reviews and editorials were excluded. Extracted data included: (1) basic study details; (2) study design; (3) sample size; (4) baseline demographics; (5) outcome data (including secondary outcomes of suicidal ideation and adverse events); and (6) stimulation parameters. Cochrane's risk of bias tool was applied. A quantitative analysis was conducted for the depression studies, using Hedge's g effect sizes. Results: A total of 24 studies (n = 377) were eligible for inclusion. Seventeen studies in depression (including three RCTs), four studies in schizophrenia (including one RCT), one study in bipolar disorder, one study in obsessive-compulsive disorder and one study in borderline personality disorder were summarized. We found no significant difference in depressive symptom reduction between MST and electroconvulsive therapy (ECT) in randomized, controlled trials (g = 0.207 towards ECT, 95% confidence interval (CI) −0.132 to 0.545, P = 0.232). We found a significant reduction in depressive symptoms overall with MST in the pooled RCT and open-label analysis (g = 1.749, CI 1.219 to 2.279, P < 0.005). It is suggested that MST has modest cognitive side effects. Conclusions: Large-scale RCTs are necessary to confirm early signals of MST as an effective intervention in psychiatric disorders with a cognitive profile that is potentially more favourable than ECT.
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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 | 0.025 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.040 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".