Manual Acupuncture at LI11, Local Points and Both for Knee Osteoarthritis: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
Objective: Knee osteoarthritis (KOA) is a common chronic degenerative joint disease, and acupuncture is an alternative therapy for KOA. This study aims to detect the effectiveness of acupuncture at LI11 in improving pain and function for KOA patients. Methods: A total of 108 patients with KOA were randomly allocated to Control Group (local points), Treatment Group A (LI11), and Treatment Group B (local points and LI11) with a treatment phase of 4 weeks and a follow-up phase of 4 weeks. Primary outcome was response rate. Secondary outcomes included Visual Analogue Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and recurrence rate. Study was registered on Chinese Clinical Trial Registry (Registered number: ChiCTR2000034926). Results: The response rate in Treatment Group A, Treatment Group B, and Control Group was 71.43%, 85.29%, and 51.53%, respectively, at Week 4, and Treatment Group B was significantly higher than Control Group (difference[98.3% CI]: 33.86[0.135,0.543], P = 0.003). Although no significant difference was found, Treatment Group A had a better response rate compared with Control Group (difference[98.3% CI]: 20.00 [-0.072, 0.472], P = 0.086). For VAS and WOMAC, there were significant differences within 3 groups at Week 4 compared with the baseline. There was a significant improvement in VAS scores and WOMAC function and pain subscales at Week 4 in Treatment Group B compared with Control Group and Treatment Group A. Conclusion: LI11 is an effective point for patients with KOA, and it could be a selection for young acupuncturists and acupuncturists who work in rural areas; however, large-sample studies are necessary to further verify results in the future.
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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 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".