Acupuncture combined with repetitive transcranial magnetic stimulation for the treatment of post-stroke cognitive impairment: a systematic review and meta-analysis with trial sequential analysis
Bibliographic record
Abstract
Objective This study aimed to comprehensively evaluate the clinical effectiveness and safety of acupuncture combined with repetitive transcranial magnetic stimulation (rTMS) in treating post-stroke cognitive impairment (PSCI) through meta-analysis and trial sequential analysis (TSA), moreover to provide an evidence-based basis for the treatment of PSCI in clinical practice. Methods The study conducted a comprehensive search of eight major domestic and international databases, including PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP and China Biology Medicine (CBM). Four English and four Chinese databases of randomized controlled trials of acupuncture combined with rTMS for the treatment of PSCI from inception until July 2025. Systematic reviews and meta-analyses were conducted based on the Cochrane systematic review method by using RevMan5.4 and Stata/MP 18.0, and trial sequential analyses were performed by TSA 0.9. Results Sixteen RCTs involving 1,058 patients were included, including 532 patients in the experimental group and 526 patients in the control group. Meta-analysis results showed that the experimental group had a higher clinical effectiveness rate in treating patients with PSCI compared to the control group [RR = 1.29, 95% CI (1.08, 1.55), p = 0.005]. The experimental group significantly improved scores on several scales: Montreal Cognitive Assessment (MoCA) [MD = 2.95, 95% CI (2.37, 3.53), p < 0.00001], Mini-Mental State Examination (MMSE) [MD = 2.89, 95% CI (2.13, 3.64), p < 0.00001], LOTCA [MD = 13.61, 95% CI (6.57, 20.65), p = 0.0002], Modified Barthel Index (MBI) [MD = 10.86, 95% CI (7.79, 13.94), p < 0.00001], Activity of Daily Life (ADL) [MD = 15.33, 95% CI (10.06, 20.61), p < 0.00001]. Also it was found to reduced the latency of P300 in the experimental group [MD = −18.18, 95% CI (−25.76, −10.61), p < 0.00001] and prolonged the amplitude of P300 [MD = 1.55, 95%CI (0.71, 2.39), p = 0.0003]. In addition, it could increase the Brain-derived Neurotrophic Factor (BDNF) level in the blood of the patients [MD = 0.93, 95%CI (0.52, 1.35), p < 0.0001], and decrease the Neuron-Specific Enolase (NSE) levels [SMD = −1.26, 95% CI (−1.59, −0.93), p < 0.00001]. There are two studies reported the adverse events. The TSA showed that the cumulative Z value of the meta-analysis of the clinical effectiveness rate, MoCA, and MMSE scales crossed the traditional and TSA boundaries, proving reliable conclusions. Conclusion Acupuncture combined with rTMS can improve cognitive function, regulate daily living ability, and regulate neurotransmitter levels in patients with PSCI, which is worthy recommended in the clinic. However, due to limitations in sample size, inclusion quality and incomplete reporting, it is worth noting that more rigorously designed and high-quality studies are needed to further validate these conclusions.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.046 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".