A systematic review and meta-analysis on the efficacy and acceptability of bilateral repetitive transcranial magnetic stimulation (rTMS) for treating major depression
Bibliographic record
Abstract
BACKGROUND: Bilateral repetitive magnetic stimulation (rTMS) is a promising novel therapeutic intervention for major depression (MD). However, clinical trials to date have reported conflicting evidence concerning its overall efficacy, which might have resulted from low statistical power. Thus, meta-analytical approaches could be useful in examining this issue by allowing the integration of findings from multiple studies and thus producing more accurate estimates of the treatment effect. METHOD: We searched the literature for randomized, double-blind and sham-controlled trials (RCTs) on bilateral rTMS for treating MD from 1995 to July 2012 using EMBASE, PsycINFO, Cochrane Central Register of Controlled Trials, SCOPUS, and ProQuest Dissertations and Theses, and from October 2008 until May 2012 using Medline. The main outcome measures were response and remission rates. We used a random-effects model, odds ratios (ORs) and the number needed to treat. RESULTS: Data were obtained from seven RCTs, totaling 279 subjects with MD. After an average of 12.9 (s.d. = 2.7) sessions, 24.7% (40/162) and 6.8% (8/117) of subjects receiving active bilateral rTMS and sham rTMS were classified as responders [OR 4.3, 95% confidence interval (CI) 1.95-9.52, p < 0.0001]. Also, 19% (23/121) and 2.6% (2/77) of subjects were remitters following active bilateral rTMS and sham rTMS, respectively (OR 6.0, 95% CI 1.65-21.8, p = 0.006). No difference between baseline mean depression scores for the bilateral and sham rTMS groups was found, and the former was comparable with the latter in terms of drop-out rates at study end. Furthermore, we did not find significant differences efficacy- and acceptability-wise between active bilateral and unilateral rTMS at study end. Finally, heterogeneity between the included RCTs was not significant, and the risk of publication bias was found to be low. CONCLUSIONS: Bilateral rTMS is a promising treatment for MD as it provides clinically meaningful benefits that are comparable with those of standard antidepressants and unilateral rTMS. Furthermore, bilateral rTMS seems to be an acceptable treatment for depressed subjects.
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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 | 0.022 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".