Clinical effect of oral Xingshi decoction combined with warming needle moxibustion in treating acute knee osteoarthritis
Bibliographic record
Abstract
Objective To evaluate the effect of Xingshi decoction combined with warming needle moxibustion combined with conventional western medicine on acute knee arthritis. Methods A total of 86 patients with acute knee arthritis were randomly divided into two groups, 43 in each group. The control group took diclofenac capsules orally and methotrexate once a week, while the observation group took Xingshi decoction and warming needle moxibustion on the basis of the control group. Both groups were treated for 2 weeks. The Rheumatoid factor (RF), high sensitive C reactive protein (hs-CRP) and IL-1β were detected by ELISA, and pain rating index (PRI), VAS and present pain intensity (PPI) were evaluated by McGill pain questionnaire (SF-MPQ). The knee function was assessed by the evaluation scale, and the curative effect was evaluated by 28 joint disease activity-erythrocyte sedimentation rate (ESR) scores. Results The total effective rate was 88.4% (38/43) in the observation group and 62.8% (27/43) in the control group. There was significant difference between the two groups (Z=2.678, P=0.007). After treatment, ESR (30.95 ± 3.14 mm/h vs. 55.13 ± 3.28 mm/h, t=34.919), RF (81.36 ± 5.13 U/ml vs. 121.73 ± 7.25 U/ml, t=29.807), hs-CRP (10.13 ± 3.12 mg/L vs. 34.26 ± 3.17 mg/L, t=35.575), IL-1β (58.13 ± 3.12 pg/ml vs. 96.76 ± 3.17 pg/ml, t=56.952) of the observation group were significantly lower than those of control group (P<0.01); and PRI, VAS and PPI scores of SF-MPQ in observation group were significantly lower than those of control group (t values were 19.661, 11.056 and 23.524, respectively, P<0.01) and the scores of walking, swelling, sense of stability, strangulation and stair-climbing were significantly higher than those of the control group (t values were 11.071, 13.464, 9.102, 9.804, 10.012, respectively, P<0.01). Conclusions The Xingshi decoction combined with warming needle moxibustion is effective in treating acute knee arthritis. It can effectively relieve pain and inflammation of patients, thus improving knee joint function. It has certain clinical application value. Key words: Arthritis; Acute pain; Xingshi decoction; Acupuncture points; Needle warming therapy; Moisten compress therapy; Comparative effectiveness research
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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 | 0.000 |
| 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) | 0.002 | 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".