Clinical Observation on Xituiyou Decoction Steam-wash Therapy for Knee Osteoarthritis with Wind-cold-dampness Arthralgia Syndrome
Bibliographic record
Abstract
Objective:To observe the clinical effect of Xituiyou decoction steam-wash therapy on knee osteoarthritis patients with wind-cold-dampness arthralgia syndrome, and explore the decoction effect on articular cavity hydrops.Methods:Atotal of 64 knee osteoarthritis patients with wind-cold-dampness arthralgia syndrome were randomly assigned to the treatment group and control group with 32 patients in each group. The treatment group received Xituiyou decoction steam-wash therapy 30 minutes each time, once a day, and the control group received external application with diclofenac diethylamine emulgel (Voltaren) three times a day, fifteen days as a course of treatment, and all patients lasted for a total of two courses of treatment. Symptom score, McGill pain score, and improvement of pathogenetic condition before and after treatment were used to evaluate the clinical effect of the decoction, and joint effusion content was detected.Results:Symptom score, pain score and joint effusion content of both groups were decreased after treatment compared with those before treatment (P<0.05), and the improvement of pathogenetic condition was better than that of before treatment (P<0.05).The decreasing amplitude of symptom score, pain score and joint effusion content in the treatment group after treatment were higher than those of the control group (P<0.05), the clinical effective rate and improvement of pathogenetic condition in treatment group were better than those of the control group (P<0.05).Conclusion:Xituiyou decoction steam-wash therapy has a positive effect on knee osteoarthritis patients with wind-cold-dampness arthralgia syndrome, and the decoction can promote the absorption of joint effusion.
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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 | 0.000 | 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 | 0.000 | 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".