[Mild cognitive impairment of stroke at subacute stage treated with acupuncture: a randomized controlled trial].
Bibliographic record
Abstract
OBJECTIVE: To verify the clinical efficacy of acupuncture for mild cognitive impairment of stroke at subacute stage. METHODS: One hundred patients at subacute stage of cerebral infarction or cerebral hemorrhage with scores of Montreal cognitive assessment (MoCA) less than 26 were randomly divided into an observation group and a control group,50 cases in each one. Based on the regulation of blood pressure and blood sugar and anticoagulation,cognitive rehabilitation training was adopted in the control group. On the basis of treatment in the control group,acupuncture was applied in the observation group. The acupoints were Baihui(GV 20), Sishencong (EX-HN 1), Shenting (GV 24), Yintang(GV 29), Hegu (LI 4) and Taichong(LR 3). Sishencong(EX-HN 1), Shenting (GV 24) and Yintang (GV 29) were connected to electroacupuncture apparatus. The treatment was given once a day,5 times a week, and 8-week treatment was acquired in the two groups. In the 4th week and the 8th week,limbs motor function, daily life ability and cognitive function were evaluated by Fugl-Meyer assessment (FMA) scale,Bathel index and MoCA scale. RESULTS: In 4 weeks and 8 weeks, the scores of FMA, Bathel index and MoCA in the two groups were improved compared with those before treatment (all P < 0.05). After 8-week treatment, the scores of Bathel index and MoCA in the observation group were better than those in the control group (both P < 0.05). CONCLUSION: Based on the cognitive rehabilitation training and the conventional treatment, acupuncture can improve the cognitive function and daily life ability of stroke patients at subacute stage 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.001 |
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".