Repetitive transcranial magnetic stimulation for major depressive disorder: basic principles and future directions
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a safe and well-tolerated intervention for major depressive disorder (MDD). Over 150 randomized controlled trials (RCTs) have been carried out, and its efficacy has been confirmed in dozens of meta-analyses. Real world data has also confirmed the effectiveness of rTMS for MDD in clinical practice, with the most recent literature indicating response rates of 40-50% and remission rates of 25-30%. In this review, we first offer an historical perspective, followed by a review of basic principles, such as putative mechanisms, procedures and protocols, stimulation targets, efficacy and durability of response, side effects, and the placebo controversy. In the second part of this review, we first discuss solutions to increase accessibility to rTMS, such as modifications to treatment equipment, protocols and setting. We continue with possible means to further increase effectiveness, such as treatment personalization and extension. We conclude by addressing the scheduling issue, with accelerated rTMS (arTMS) as a possible solution.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".