The effectiveness of transcranial magnetic stimulation for dysphagia in stroke patients: an umbrella review of systematic reviews and meta-analyses
Bibliographic record
Abstract
Numerous studies have explored the use of repetitive Transcranial Magnetic Stimulation (rTMS) intervention in post-stroke dysphagia. The primary aim of this umbrella review was to appraise the methodological quality of systematic reviews (SRs), with and without meta-analyses (MAs), that synthesized the findings of randomized controlled trials (RCTs) exploring the effectiveness of rTMS in the management of dysphagia post-stroke. A secondary aim of was to evaluate the consistency and reliability of translational implications of rTMS for swallowing recovery after stroke across these SRs and MAs. We searched several databases from inception to the 14th of May 2023, to identify SRs and MAs that examined the effectiveness of rTMS in the management of dysphagia post-stroke. The methodological quality of the included studies was evaluated utilizing the AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews) instrument. To investigate the extent of literature overlap among the primary studies included in the SRs, the Graphical Overview of Evidence (GROOVE) was utilized. Of the 19 SRs that were identified, two studies received low quality ratings, while the rest (17) were rated with critically low quality based on the AMSTAR 2 rating. A high literature overlap across the SRs was observed. In all SRs and MAs reviewed, there was a consistent presence of at least some significant evidence supporting the effectiveness of rTMS in enhancing swallowing outcomes for individuals with dysphagia post-stroke, that is, all MAs reported at least a moderate overall effect in favor of rTMS (SMD range = [0.59, 6.23]). While rTMS shows promise for improving dysphagia post-stroke, the current evidence remains limited and inconclusive due to the methodological flaws observed in the published SRs and their respective MAs on the topic so far. Concerning the limitations of our study, language restrictions and methodological shortcomings may affect the generalizability of our findings.
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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 | 0.052 | 0.156 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.025 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".