Crossbow needle therapy of the Miao ethnic minority group for knee osteoarthritis: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) is commonly seen and has a high occurrence in the middle-aged and elderly. It is characterized by the degeneration and secondary bone hyperplasia of the articular cartilage; the pathologic changes are irreversible. Therefore, treatment of KOA is mainly focused on relieving pain, reducing inflammation, improving or restoring joint function, delaying disease progression, and increasing quality of life. Crossbow needle therapy of the Miao ethnic minority group is intended for KOA treatment and has been widely used. Studies of small sample size have seen significant improvement on pain relief, stiffness, and joint function. METHODS/DESIGN: The trial is a randomized, multicenter, parallel, non-inferiority study. Three hundred and six patients will be randomly assigned to a crossbow needle group (n = 153) and an acupuncture group (n = 153). Patients in each group will receive treatment every other day, three times a week, 20 times in total. Follow-up will be conducted 15 days and 30 days after treatment. The primary outcome will be the Western Ontario and McMaster Osteoarthritis Index (WOMAC) score at baseline, the end of treatment, first follow-up, and second follow-up. The secondary outcomes will include Lysholm knee score, Japanese Orthopedic Association (JOA) knee score, visual analogue scale (VAS), and the MOS 36-item short-form health survey (SF-36). DISCUSSION: The results of the trial will compare the efficacy on KOA between crossbow needle group and acupuncture group and will be expected to make a systematic and objective evaluation of crossbow needle therapy. TRIAL REGISTRATION: ChiCTR, ChiCTR-INR-16008032 . Registered on 12 March 2016.
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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 | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.007 |
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".