Repetitive Transcranial Magnetic Stimulation for the Treatment of Resistant Depression: A Scoping Review
Bibliographic record
Abstract
Treatment-resistant depression (TRD) is associated with significant disability, and due to its high prevalence, it results in a substantive socio-economic burden at a global level. TRD is the inability to accomplish and/or achieve remission after an adequate trial of antidepressant treatments. Studies comparing repetitive transcranial magnetic stimulation (rTMS) with electroconvulsive therapy (ECT) and pharmacotherapy have revealed evidence of the therapeutic efficacy of rTMS in TRD. These findings suggest a crucial role for rTMS in the management of TRD. This article aims to conduct a comprehensive scoping review of the current literature concerning the use of rTMS and its therapeutic efficacy as a treatment modality for TRD. PubMed, PsycINFO, Medline, Embase, and Cinahl were used to identify important articles on rTMS for TRD. The search strategy was limited to English articles within the last five years of data publication. Articles were included if they reported on a completed randomized controlled trial (RCT) of rTMS intervention for TRD. The exclusion criteria involved studies with rTMS for the treatment of conditions other than TRD, and study and experimental protocols of rTMS on TRD. In total, 17 studies were eligible for inclusion in this review. The search strategy spanned studies published in the last five years, to the date of the data search (14 February 2022). The regional breakdown of the extracted studies was North American (n = 9), European (n = 5), Asian (n = 2) and Australian (n = 1). The applied frequencies of rTMS ranged from 5 Hz to 50 Hz, with stimulation intensities ranging from 80% MT to 120% MT. Overall, 16 out of the 17 studies suggested that rTMS treatment was effective, safe and tolerated in TRD. For patients with TRD, rTMS appears to provide significant benefits through the reduction of depressive symptoms, and while there is progressive evidence in support of the same, more research is needed in order to define standardized protocols of rTMS application in terms of localization, frequency, intensity, and pulse parameters.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".