Repetitive transcranial magnetic stimulation in conjunction with scalp acupuncture in treating poststroke cognitive impairment: a protocol for systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Approximately 70% of patients with stroke experience varying degrees of cognitive impairment, which imposes a substantial direct and indirect socioeconomic burden. Previous studies have shown that scalp acupuncture (SA) or repetitive transcranial magnetic stimulation (rTMS) in combination with other therapies is effective for poststroke cognitive impairment (PSCI). Limited by interstudy heterogeneity and the limited number of included studies, there is insufficient evidence of the efficacy of rTMS in combination with SA in treating PSCI. Therefore, this protocol aims to investigate the effectiveness of rTMS in conjunction with SA for patients with PSCI through a comprehensive meta-analysis. METHODS AND ANALYSIS: This study will undertake a comprehensive search across nine distinct databases (Web of Science, Embase, Cochrane Library, PubMed, China National Knowledge Infrastructure, Wanfang Data, China Science and Technology Journal Database, China Biology Medicine and SCOPUS). The primary outcome will encompass the Montreal Cognitive Assessment and the Mini-Mental State Examination. The secondary outcomes are the modified Barthel Index, the Rivermead Behavioral Memory Test and the Digit Span Test. The bias risk assessment tool from the Cochrane Handbook for Systematic Reviews of Interventions will be used to evaluate bias risk, and the GRADE will be applied to gauge the quality of evidence. Furthermore, we plan to perform an analysis of subgroups to investigate the heterogeneity, employ the leave-one-out approach for sensitivity evaluation and use funnel plots and Egger's test to determine publication bias, respectively. ETHICS AND DISSEMINATION: Ethical approval is not required in systematic review and meta-analysis. The review will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42024571762.
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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 | 0.065 | 0.088 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.027 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".