The clinical efficacy of ligustrazine in the treatment of knee osteoarthritis
Bibliographic record
Abstract
Objective: To investigate the efficacy of ligustrazine in the treatment of mild and moderate knee osteoarthritis. Methods: This prospective study recruited 69 patients with knee osteoarthritis, who were randomly divided into a control group (n=34) and a treatment group (n=35). The patients in the control group were injected with hyaluronic acid in their joint cavities for 6 weeks. Based on the treatment in the control group, the patients in the treatment group took ligustrazine phosphate tablets orally for 6 weeks. The clinical efficacy and the patients' Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were observed before and after they were treated. The changes in the TNF-alpha, IL-1, IL-6, and MMP-13 levels in the joint fluid were measured. Results: After treatment, the efficacy of the treatment in the treatment group was better than the efficacy in the control group (P<0.05). The patients' WOMAC scores in the treatment group were better than the patients' scores in the control group after they were treated, but there was no significant difference (P>0.05). The patients' IL-1 and IL-6 levels in the treatment group were higher than the levels in the control group (P<0.01). The incidence of adverse reactions in the treatment group was lower than it was in the control group (P<0.05). Conclusion: Ligustrazine has a good clinical efficacy in the treatment of mild and moderate knee osteoarthritis and can improve the condition of knee joint activity and effectively reduce the levels of IL-1 and IL-6 in joint fluid as well as reduce the incidence of adverse reactions, indicating that ligustrazine can be used as a safe and effective treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".