Clinical Efficacy of Xiaoyusan Plaster in Treatment of Knee Osteoarthritis
Bibliographic record
Abstract
Objective To observe the clinical efficacy and safety of Xiaoyusan Plaster in the treatment of knee osteoarthritis(KOA).Methods Forty patients with KOA were randomly divided into treatment group(n=26) and control group(n=14).The treatment group was treated with Xiaoyusan Plaster and the control group was treated with Voltaren Gel.The course of treatment was 6 weeks.Pain and function were measured using a visual analogue scale(VAS) and a Western Ontario and McMaster Universities(WOMAC) total score scale.The concentrations of cartilage oligomeric matrix protein(COMP)and collagen type Ⅱ degradation C-terminal peptide(CTX-Ⅱ)measured using ELISA were served as cartilage metabolism indicators.Results Scores of VAS(t=11.7,P0.001),WOMAC(t=6.1,P0.001) and concentrations of COMP(t=7.2,P0.001)、CTX-Ⅱ(t=1.2,P=0.24) were significantly reduced in the treatment group after 6 weeks.Scores of VAS(t=7.3,P0.001)、WOMAC(t=5.1,P0.001) and concentrations of COMP(t=8.8,P0.001),CTX-Ⅱ(t=0.82,P=0.43) were also reduced in the control group.Pain and function of joint were significantly improved in the two groups.The differences of VAS,WOMAC,CTX-Ⅱ were not significant between the two groups,but the difference of COMP was significant between the two groups(t=2.3,P=0.03).Adverse events were not found in both groups,excepting local rash in two cases.Conclusion Xiaoyusan Plaster can significantly improve the clinical symptoms and the joint function of KOA patients without serious adverse reaction,and it has a certain application value in the treatment of KOA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".