Comparative Efficacy and Safety of Benjakul vs. Naproxen in Primary Knee Osteoarthritis: A Multicenter RCT
Bibliographic record
Abstract
Objective: To compare the efficacy and safety of Benjakul (BJK) and Naproxen (NPX) for treating primary knee osteoarthritis (KOA) in a multicenter randomized trial. Materials and Methods: Three hundred fifty participants were randomly assigned to receive either BJK or NPX for four weeks. The primary endpoint was the change in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score. Similarly, secondary endpoints including the 40-meter fast-paced walk test (40mFPWT), Timed Up and Go test (TUG), WOMAC, Knee Injury and Osteoarthritis Outcome Score (KOOS), and the 12-item Short Form Survey (SF-12V2). Statistical analysis revealed comparable improvements across all measures (p≤0.05), confirming treatment equivalence. Safety evaluations were performed through laboratory tests. Results: BJK showed notable improvements in pain reduction and functional outcomes compared to NPX, with significant improvements in VAS, TUG, total WOMAC score, and individual categories of the KOOS score at 14 and 28 days. The adverse event rate was dry lips and throat in 8.2% in the BJK group and 6.5% in the NPX group with abdominal discomfort, and constipation being the most common side effect. Conclusion: BJK demonstrates comparable efficacy and safety to NPX in treating KOA, with no significant safety concerns identified in the clinical trial. This suggests that BJK can be recommended as a natural anti-inflammatory drug for patients suffering from knee osteoarthritis.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".