Efficacy and Safety of Cheong-A-Won Gagambang (JCE003) on Knee Osteoarthritis: Randomized Controlled Pilot Trial
Bibliographic record
Abstract
Background: The aim of this study was to evaluate the effectiveness and safety of Cheong-A-Won Gagambang (JCE003) treatment for degenerative knee osteoarthritis.Methods: This was a single-center, randomized, double-blind, placebo-controlled pilot clinical trial. There were 36 adults with degenerative knee osteoarthritis who were randomly allocated into JCE003 1,000 mg, JCE003 2,000 mg, or the placebo group (in a 1:1:1 ratio). The participants received 12 weeks of treatment and had scheduled tests every 6 weeks. The primary outcomes were measured using the Korean Western Ontario and McMaster Universities scale, and the secondary outcomes were measured using the visual analog scale, European quality of life-5-dimensions, patient global impression of change, C-reactive protein, and erythrocyte sedimentation rate. Changes between baseline scores and scores following study completion were analyzed.Results: There were 29 participants whose data were analyzed in this study. The change of Korean Western Ontario and McMaster Universities, visual analog scale, European quality of life-5-dimensions scores showed significant improvement in the JCE003 1,000 mg group. The change of patient global impression of change was significantly improved in the placebo group. There were 14 adverse events, but there was no clinically significant relationship with the intake of JCE003 compared with the placebo.Conclusion: Taking JCE003 may be effective at improving knee pain in patients with degenerative knee osteoarthritis and appears to be safe. Based on this study, the concentration and feasibility of the test group may be used when conducting a large-scale clinical trial of degenerative knee osteoarthritis in the future.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".