Systematic review and network meta-analysis of effects of noninvasive brain stimulation on post-stroke cognitive impairment
Bibliographic record
Abstract
Objective: To systematically assess the effects of Noninvasive Brain Stimulation (NIBS) on post-stroke cognitive impairment (PSCI) and to compare the efficacy of two different NIBS. Methods Computer searches of PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Chinese Biomedical literature Service System (SinoMed), and Wanfang Database were conducted using a combination of free words and subject terms. The search was conducted from the database creation date to 27 November 2022. The risk of bias in the included literature was assessed using the Cochrane Risk Assessment Scale. The quality of the included literature was assessed using the physiotherapy evidence database (PEDro) scale. A standard meta-analysis of study data for each outcome indicator was performed using RevMan 5.4 software. Network meta-analysis was performed using State 14.0 according to the Bayesian framework. Results A total of 18 studies involving 809 patients were included. Meta-analysis shows NIBS significantly improved montreal cognitive assessment (MoCA) scores (standardized mean difference [SMD] = 0.76, 95% confidence interval (CI) 0.49–1.02, P < 0.05), mini-mental state examination (MMSE) scores (SMD = 0.72, 95% CI 0.25–1.20, P < 0.05), and modified barthel index (MBI) and functional independence measurement (FIM) scores (SMD = 0.33, 95% CI 0.11–0.54, P < 0.05) in patients with PSCI. The surface under the cumulative ranking curve (SUCRA) of different NIBS in improving MoCA scores were in the order of transcranial direct current stimulation (tDCS) (SUCRA = 92.4%) and transcranial magnetic stimulation (TMS) (SUCRA = 57.6%). The SUCRA of different NIBS in improving MMSE scores were in the order of tDCS (SUCRA = 81.6%) and TMS (SUCRA = 67.3%). The SUCRA of different NIBS in improving MBI and FIM scores were in the order of tDCS (SUCRA = 78.6%) and TMS (SUCRA = 65.3%). Conclusion The available evidence suggests that NIBS improves cognitive impairment. tDCS appeared more effective than TMS for cognitive function and activities of daily living in PSCI patients. Limited by the number of included studies, more large-sample, multicentre, double-blind, high-quality randomized controlled clinical trials are needed to further confirm this study's results. Systematic review registration https://www.crd.york.ac.uk/prospero/ , identifier: CRD42022372354 .
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.036 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".