Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Depression: A Systematic Review and Metaanalysis
Bibliographic record
Abstract
OBJECTIVE: Systematic reviews show that repetitive transcranial magnetic stimulation (rTMS) is superior to sham control conditions in patients with major depressive disorder, but the clinical relevance is not clear. None have specifically examined outcomes in patients with treatment-resistant depression (TRD). METHOD: A systematic review was conducted by identifying published randomized controlled trials of active rTMS, compared with a sham control condition in patients with defined TRD (that is, at least one failed trial). The primary outcome was clinical response as determined from global ratings, or 50% or greater improvement on a rating scale. Other outcomes included remission and standardized mean differences in end point scores. Metaanalysis was conducted for absolute risk differences using random effects models. Sensitivity and subgroup analyses were also conducted to explore heterogeneity and robustness of results. RESULTS: A total of 24 studies (n = 1092 patients) met criteria for quantitative synthesis. Active rTMS was significantly superior to sham conditions in producing clinical response, with a risk difference of 17% and a number-needed-to-treat of 6. The pooled response and remission rates were 25% and 17%, and 9% and 6% for active rTMS and sham conditions, respectively. Sensitivity and subgroup analyses did not significantly affect these results. Dropouts and withdrawals owing to adverse events were very low. CONCLUSIONS: For patients with TRD, rTMS appears to provide significant benefits in short-term treatment studies. However, the relatively low response and remission rates, the short durations of treatment, and the relative lack of systematic follow-up studies suggest that further studies are needed before rTMS can be considered as a first-line monotherapy treatment for TRD.
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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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".