Clinical Efficacy of Deep Transcranial Magnetic Stimulation in Psychiatric and Cognitive Disorders: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Transcranial magnetic stimulation (TMS) is a widely used noninvasive brain stimulation technique for psychiatric and cognitive disorders. In recent years, deep TMS (dTMS) has shown promise as an enhanced form of TMS able to stimulate deeper brain structures and target broader networks. Various magnetic Hesed-coil (H-coil) designs-a novel feature of dTMS-have been used to stimulate brain regions implicated in the pathophysiology of specific psychiatric and cognitive disorders, thereby producing therapeutic effects. Given the novelty of dTMS in psychiatry, little is known about the clinical efficacy of dTMS across psychiatric and cognitive disorders-that is, whether dTMS performs superiorly to sham or control. OBJECTIVE: In this paper, we outline a protocol for a systematic review investigating the clinical efficacy of dTMS. The primary objective is to conduct a systematic review of the literature on dTMS for psychiatric and cognitive disorders and, if feasible, a meta-analysis to compare the efficacy of active dTMS versus sham/control for psychiatric disorders. Dementia and related cognitive disorders will also be examined. A secondary objective will be to examine subgroup differences (by age, sex, H-coil design, and dTMS parameters [ie, pulses per session, percentage of motor threshold, etc]) to evaluate whether dTMS differentially influences clinical outcomes based on these factors. METHODS: A comprehensive search of the APA PsycINFO, Embase, MEDLINE, and PubMed databases will be conducted using keywords such as "H-coil" and "dTMS." Two authors (AD and MD) will be responsible for screening relevant articles, assessing article eligibility (according to predetermined inclusion and exclusion criteria), and data extraction. All included articles will undergo a quality and risk of bias assessment. Data from included articles will be summarized qualitatively in a systematic review. If a sufficient number of equivalent studies are available, a meta-analysis will be performed to (1) determine the effect of active versus sham dTMS (or another control arm) across psychiatric and cognitive disorders, and (2) examine subgroup effects of clinical outcomes. RESULTS: The preliminary search rendered a total of 1134 articles from the APA PsycINFO, Embase, and MEDLINE databases. After full-text screening, 21 eligible articles remained. One additional article was identified from the references section of an existing systematic review. In total, 22 eligible articles were included. Data extraction and quality of assessment procedures are ongoing. CONCLUSIONS: We will outline the evidence relating to the clinical efficacy of dTMS in various psychiatric and cognitive disorders. The results of the prospective systematic review will provide clinicians with valuable insight into the clinical (ie, participant age, sex, psychiatric or cognitive disorder, etc) and methodological factors (ie, H-coil design, dTMS parameters, etc) which may contribute to dTMS efficacy, and thereby may assist clinicians in their decision to prescribe dTMS for specific psychiatric and cognitive disorders. TRIAL REGISTRATION: PROSPERO CRD42022360066; https://tinyurl.com/5ev6byrn. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45213.
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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 | 0.039 | 0.049 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.018 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.058 | 0.005 |
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".