Study on efficacy and safety of Tong-luo Qu-tong plaster treatment for knee osteoarthritis: study protocol for a randomised, double-blind, parallel positive control, multi-center clinical trial
Bibliographic record
Abstract
Abstract Background: Knee osteoarthritis (KOA) is a common chronic musculoskeletal disorder that seriously affect quality of life. Patients with KOA frequently develop one or more of the typically following symptoms: joint pain, stiffness, joint friction noise, impaired functionality. Traditional Chinese medicines (TCM) have showed a superior effect and peculiar advantage on the treatment of KOA, among TCMs, the Tong-luo Qu-tong plaster is the convenient and most commonly used method in China to improve symptoms including pain, stiffness and limited mobility in patients with KOA, as it causes few adverse effects. But there is a lack of high quality of clinical evidences to support the therapeutic effect that Chinese adhesive plaster can relieve pain and stiffness. The purpose of this study will be to evaluate the efficacy and safety of Tong-luo Qu-tong plaster in patients with KOA. Methods/Design: This study will be a randomised, double-blind, parallel positive control, multi-center clinical trial, a non-inferiority trial design was adopted. A total of 2000 participants older than 40 years with KOA, will be randomly allocated into a experimental group (n=1500) and a control group (n=500). All participants will receive a conventional conservative treatment lasted for 14 days as two courses, daily 1 time. Tong-luo Qu-tong plaster will be administered externally to participants in the experimental group, while the control group will receive a Qi-zheng Xiao-tong plaster. The outcome of the total Western Ontario and McMaster Universities Arthritis Index scores, TCM syndrome quantitative score, visual analog scale scores will be measured during the assessment visits (baseline and 1-, 2-week follow-up). In addition, adverse events concerning clinical symptoms and signs as well as laboratory tests will be documented during clinical trials. Discussion: This study will be a randomized, double-blind, parallel positive control trial to further evaluate the effectiveness and safety of Tong-luo Qu-tong plaster for patients with KOA in nine medical centers compared with control group, it is expected that the patients with KOA will benefit from this study.
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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 | 0.021 | 0.015 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 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".