Effect of Baduanjin exercise on cognitive function in patients with post-stroke cognitive impairment: a randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To investigate the effectiveness and safety of Baduanjin training on the cognitive function in stroke survivors with cognitive impairment. DESIGN: A randomized, two-arm parallel controlled trial with allocation concealment and assessors blinding. SETTING: Community centre of Fuzhou city, China. SUBJECTS: A total of 48 participants were recruited and randomly allocated into the Baduanjin exercise intervention or control group. INTERVENTIONS: The control group maintained original medication and rehabilitation treatment. The Baduanjin training group received 24-week Baduanjin training with a frequency of three days a week and 40 minutes a day based on original medication and rehabilitation treatment. MAIN OUTCOME MEASURES: The primary outcome was global cognitive function. Secondary outcome measures included the specific domains of cognition (i.e. memory, processing speed, execution, attention and visuospatial ability) and activities daily living. RESULTS: = 19) participants completed 24-week treatment and data collection. Mean differences between groups at 24-week treatment were statistically significant for global cognitive function (MoCA: 2.54 (0.91 to 4.16)), execution (TMT-A: -42.4 (-75.0 to -9.8); TMT-B: -71.3 (-130.6 to -12.1)), memory (immediate recall: 2.11 (0.49 to 3.73); short-term delayed recognition: 2.47 (0.58 to 4.35) and long-term delayed recognition: 1.68(0.18 to 3.17)), attention (response time of alertness: -245.5 (-387 to -104)) and activities of daily living (modified Barthel Index). CONCLUSION: Regular Baduanjin training is associated with less loss of cognitive function in patients after stroke.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".