[Acupotomy at trigger points combined with meridian sinew manipulation in treatment of knee osteoarthritis: a randomized controlled trial].
Bibliographic record
Abstract
OBJECTIVES: To observe the clinical efficacy of acupotomy at trigger points combined with meridian sinew manipulation in treatment of early and mid-term knee osteoarthritis (KOA), and investigate whether its therapeutic mechanism is related to the regulation of inflammatory response. METHODS: Seventy-four patients with early and mid-term KOA were randomly divided into the control group (37 cases, with 2 cases dropouts) and the observation group (37 cases, with 1 case dropout). The control group was treated with meridian sinew manipulation for 30 min each time, 5 times a week, for 4 consecutive weeks. The observation group was given acupotomy at trigger points on the basis of the treatment of control group, once a week, for 4 consecutive weeks. Western Ontario and McMaster University osteoarthritis index (WOMAC) scores, short-form McGill pain questionnaire (SF-MPQ) scores, the medical outcome 36-item short form health survey (SF-36) scores, serum inflammatory factors content before and after treatment were compared between the two groups. The clinical efficacy were assessed after the treatment. RESULTS: <0.05). CONCLUSIONS: Acupotomy at trigger points combined with meridian sinew manipulation can significantly improve the clinical symptoms such as joint pain, stiffness and limited activity in patients with KOA, improve the quality of life, and its mechanism may be related to reducing the inflammatory response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.008 | 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".