Effectiveness of Diacerein in Primary Knee Osteoarthritis
Bibliographic record
Abstract
Objective: To determine role of diacerein among the patient with primary knee osteoarthritis (KOA). Study Design: An observational cohort study. Place and Duration: Department of orthopedic surgery, Sughra Shafi Medical Complex, Narowal from June 2021 to May 2022. Materials and Methods: A total of 100 patients of either gender visiting outpatient department with primary KOA aged 50-75 years were enrolled. Patients were assessed as per Western Ontario and McMaster Universities Arthritis Index (WOMAC) and visual analogue scale (VAS). Diacerein was prescribed 100 mg two times a day for a total duration of six months. WOMAC and VAS were noted before and after completion of the 6 months follow up period. Results: In a total of 100 patients, 56 (56.0%) were female. Mean age was 63.58 ± 6.42 years while mean BMI was 29.46±3.42 kg/m2. There were 50 (50.0%) patients who belonged to middle socioeconomic status. Grade of KOA was II in 54 (54.0%) patients. Baseline WOMAC score was 45.12±6.68 while baseline VAS was noted to be 6.81±2.76. At the end of the 6-month treatment period, 83 patients completed the treatment span and so were included in the final analysis. It was found that significant reduction in both WOMAC score (p<0.0001) and VAS (p<0.0001) were found among the studied patients. Practical Implications: Diacerein seems to be a good option for relief in symptoms against patients suffering with primary knee osteoarthritis but further randomized trials should be conducted to verify the findings of this study. Conclusion: Diacerein resulted in significant improvement in the mean WOMAC and VAS scores after six months therapy. Keywords: Diacerein, improvement, Osteoarthritis Knee, VAS, WOMAC
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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) | 0.000 | 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".