Assessing the Efficacy of Repetitive Transcranial Magnetic Stimulation in the Management of Treatment Resistant Depression: A Scoping Review
Bibliographic record
Abstract
Introduction Treatment-resistant depression (TRD) is the failure to accomplish and/or achieve remission after an adequate trial of different classes of antidepressant treatments. TRD presents with significant disability and high prevalence. It results in a substantive socio-economic burden at the community and global levels. TRD. Studies comparing pharmacotherapy and electroconvulsive therapy with repetitive transcranial magnetic stimulation (rTMS) have demonstrated evidence in support of the therapeutic efficacy of rTMS in TRD. Objectives This comprehensive scoping review aimed to explore and garner information in the literature regarding the crucial role of rTMS and its therapeutic efficacy as a treatment modality for TRD. Methods Electronic data searches in PubMed, PsycINFO, Medline, Embase, and Cinahl were conducted to identify important articles on rTMS for TRD. The data search strategy was limited to articles written in English and published within the last five years, to the date of the data search (February 2022). Articles were reviewed if they reported on a completed randomized controlled trial of rTMS treatment in TRD. Articles were excluded if they were protocols of rTMS on TRD and studies with rTMS for the treatment of conditions other than TRD. The review process was reported using the PRISMA Extension for Scoping Reviews (PRISMA-ScR). Results In total, 17 studies met the eligibility criteria for this review. The geographical breakdown of the extracted studies consisted of North America (n = 9), Europe (n = 5), Asia (n = 2), and Australia (n = 1). The frequencies of rTMS applied in the various studies ranged from 5 Hz to 50 Hz, with stimulation intensities ranging from 80% MT to 120% MT. Overall, 16 out of the 17 studies demonstrated evidence that suggested rTMS treatment was effective, safe, and tolerated in the management of patients with TRD. Conclusions Overall, rTMS appeard to provide significant therapeutic benefits for patients with TRD through the reduction of depressive symptoms. However, while there is progressive evidence in support of rTMS in TRD, more research is needed to define the standardized protocols of rTMS application in terms of localization, frequency, intensity, and pulse parameters to realize its full potency in TRD. Disclosure of Interest None Declared
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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 | 0.021 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".