Systematic review and meta-analysis of randomized controlled trials assessing the impact of Baduanjin exercise on cognition and memory in patients with mild cognitive impairment
Bibliographic record
Abstract
Objective: To determine the effectiveness of Baduanjin exercise in improving cognition and memory in patients with mild cognitive impairment. Data sources: Relevant English- and Chinese-language studies published until 15 th September 2020 were retrieved from the PubMed, Web of Science, Cochrane Library, Embase, EBSCOhost, OVID, National Knowledge Infrastructure, WANFANG DATA, VIP Information, and SinoMed databases. Review methods: Randomized controlled trials assessing Baduanjin exercise in patients with mild cognitive impairment were included. Two researchers independently identified eligible studies and extracted data. Risk-of-bias assessment was performed using the Cochrane Risk of Bias Tool. Results: This study included 16 randomized controlled trials (1054 participants) from China that used Chinese versions of standardized tests. Most studies had no significant bias, and only one study had a high risk of bias in the random allocation category. Compared with conventional therapy alone, Baduanjin plus conventional therapy significantly improved the Montreal Cognitive Assessment and Mini-Mental State Examination scores after 6 months of treatment ( P < 0.00001 for both), significantly decreased the tau/Aβ 1–42 ratio in the cerebrospinal fluid ( P < 0.00001), and significantly improved some dimensional scores on the Wechsler Memory Scale and the auditory verbal learning test scores at 6 months ( P < 0.05 for all). Conclusion: Compared with conventional therapy, Baduanjin plus conventional therapy significantly improved cognitive and memory function in patients with mild cognitive impairment.
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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 | 0.060 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".