Effects of multi-site non-invasive brain stimulation on cognitive impairment after stroke: a systematic review and meta-analysis
Bibliographic record
Abstract
Objective Post-stroke cognitive impairment (PSCI) is one of the core symptoms following a stroke, which severely affects the prognosis of patients. This systematic review and meta-analysis aim to explore the effectiveness and safety of multi-site non-invasive brain stimulation (MS-NIBS) in enhancing the cognitive function of PSCI patients. Methods A comprehensive search was conducted in multiple databases, including MEDLINE (PubMed), Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Database for Chinese Technical Periodicals, and Chinese Biomedical Literature Database (CBM). The search was performed up to 18 January 2025. The inclusion criteria for this meta-analysis were randomized controlled trials (RCTs) of MS-NIBS for PSCI. The primary outcome measure was the change in the global cognitive scale, while the secondary outcomes focused on improvements in attention, memory, visuospatial perception, and activities of daily living. The Cochrane Risk of Bias Tool was used to assess the quality of each eligible study. Meta-analysis and bias analysis were performed using RevMan (Version 5.3). Results A total of 6 RCTs involving 416 samples were included in this paper. The findings from the primary outcomes revealed that the MS-NIBS group had significantly higher scores on the Montreal Cognitive Assessment (MOCA) of the cognitive composite scale (MD = 1.84, 95% CI = 1.21–2.48, p < 0.00001, I2 = 36%) compared to the single-site non-invasive brain stimulation (SS-NIBS) group. As for the secondary outcome measures, as shown by the Digit Span Test (DST) forward recall (MD = 0.94, 95% CI = −1.11 to 2.98, p = 0.37, I2 = 97%), DST backward recall (MD = 0.03, 95% CI = −0.24 to 0.29, p = 0.85, I2 = 0%), Clock Drawing Test (CDT) (MD = 1.65, 95% CI = 0.77–2.53, p = 0.0003, I2 = 54%), Trail Making Test (TMT) (MD = 4.2, 95% CI = 2.71–5.69, p < 0.00001, I2 = 14%), and Modified Barthel Index (MBI) for activities of daily living assessment (MD = 3.71, 95% CI = −4.77 to 12.20, p = 0.39, I2 = 75%), the MS-NIBS group showed improvements in visuospatial and trail-making test abilities. Subgroup analysis of the main outcome demonstrated that multi-site transcranial magnetic stimulation (MS-TMS) (MD = 2.1, 95% CI = 1.38–2.81, p < 0.00001, I2 = 48%) and the combined treatment of TMS and transcranial direct current stimulation (tDCS) (MD = 1.91, 95% CI = 0.81–3.01, p = 0.0007, I2 = 0%) exhibited superior efficacy compared to SS-NIBS. Conclusion This meta-analysis provides evidence supporting that MS-NIBS, as an emerging neuromodulatory tool, is superior to SS-NIBS in improving the overall cognitive abilities of stroke patients. However, given the limited number of included studies, it is necessary to further validate these findings through large-scale, multi-center, double-blind, and high-quality RCTs. Systematic review registration https://www.crd.york.ac.uk/prospero/ , CRD42025640015.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.035 |
| Bibliometrics | 0.006 | 0.006 |
| 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".