Effect of acupuncture on vascular cognitive impairment (VCI): A randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Vascular cognitive impairment (VCI) is a condition associated with cerebrovascular diseases, which causes a heavy burden on both individuals and society. Acupuncture has been used extensively in China to treat these complications. However, the therapeutic efficacy of this treatment remains uncertain. Consequently, we aimed to investigate the clinical effects of acupuncture on VCI. METHODS: Patients (n = 97) were randomly divided into the intervention (n = 48) and the control (n = 49) groups. The intervention group was given donepezil hydrochloride orally once a day for 4 weeks, and the intervention group was combined with acupuncture treatment on the basis of control group once daily, 6 days a week, for a total of 4 weeks. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment scores were performed before the intervention and after the intervention (4 weeks post-intervention). The levels of interleukin (IL)-1β and IL-6 were measured before the intervention and after the intervention (4 weeks post-intervention). Finally, the clinical effective rate was calculated according to the MMSE scores before and after intervention. RESULTS: Following the intervention, significant differences were observed between the intervention and control groups. After 4 weeks, MMSE and Montreal Cognitive Assessment scores were significantly increased (P < .001), and IL-1β and IL-6 levels were significantly decreased (P < .001). CONCLUSION: Acupuncture treatment can improve the cognitive function of patients with VCI and decrease the levels of IL-1β and IL-6. These findings strongly support the efficacy of acupuncture as a therapeutic intervention in patients with VCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".