[Clinical study of fire acupuncture with centro-square needles for knee osteoarthritis].
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy difference between fire acupuncture with centro-square needles (FACSN) and filiform needling (FN) for knee osteoarthritis (KOA). METHODS: points, Xuehai (SP 10), Liangqiu (ST 34), Neixiyan (EX-LE 4), Dubi (ST 35), Zusanli (ST 36), Yanglingquan (GB 34) and Yinlingquan (SP 9) were selected in the two groups. The FACSN group was treated with FACSN, and three acupoints were selected for each treatment; the FN group was treated with FN, and all the acupoints were selected for each treatment. The cupping treatment was given after acupuncture in the two groups. The treatment was given once every other day, without treatment on Sundays. The treatment was given three times a week, 6 times as one course; totally 2 courses were provided. The visual analogue scale (VAS) and Western Ontario and McMaster Universities Arthritis Index (WOMAC) were observed in the two groups before treatment, two weeks, four weeks into treatment and at one-month follow-up visit. In addition, the comprehensive efficacy was compared between the two groups. RESULTS: <0.01), respectively. CONCLUSIONS: Fire acupuncture with centro-square needles has relatively high cured and remarkable effective rate for KOA, with rapid onset; as for pain relief, the efficacy is superior to filiform needling.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".