Equivalent beneficial effects of unilateral and bilateral prefrontal cortex transcranial magnetic stimulation in a large randomized trial in treatment-resistant major depression
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation treatment (rTMS) is an effective treatment for depression but the optimal methods of administration have yet to be determined. Recent studies have produced conflicting results as to whether unilateral rTMS is more or less effective than sequentially applied bilateral rTMS. To address this we conducted a trial comparing sequential bilateral rTMS to right-sided unilateral rTMS using a priming protocol. Patients with treatment-resistant depression (n = 179) were enrolled in a two-arm randomized controlled trial across a 4-wk time period. The primary outcome assessment was the Hamilton Depression Rating Scale. Overall, there was a substantial response rate of >50% (and a 40% remission rate); however, there were no significant differences in clinical response between the two treatment groups. rTMS was well tolerated with a very low discontinuation rate. There was no relationship between response in the current trial and previous response, or non-response, to electroconvulsive therapy. We found no significant differences in clinical response between sequential bilateral rTMS and right-sided unilateral rTMS applied with a priming protocol. The results of this study do not support superior efficacy of bilateral rTMS and instead suggest that other approaches should be explored to increase treatment efficacy.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".