Comparison Of Diacerein-Ginger With Diacerein Alone In Treating Knee Osteoarthritis
Bibliographic record
Abstract
Objective: To compare clinical efficacy of diacerein-ginger with diacerein alone in treating knee osteoarthritis. Duration and place of study: It was a randomized clinical trial conducted from 21st September 2018 to 31stMarch 2019, in medical OPD of a private hospital in Karachi. Methodology: 60 diagnosed patients of knee osteoarthritis were included in this study. Male and female patients 50 years of age, fulfilling the inclusion criteria and after written informed consent experienced a wash-out period of 72 hours. These patients were systematically randomized into 2 groups each having 30 members. Group A received capsule Diacerein 50mg + capsule Ginger 550 mg twice daily and group B received capsule Diacerein 50mg twice daily, for 12 weeks. Parameters checked at 0, 6 and 12 weeks were: Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index, pain at rest and movement (Visual Analogue Scale). Comparison of the two groups was done by independent t-test. Results: Among 60 patients; 20 (33.33 %) were males and 40 (66.66%) were females. 4 patients in group A and 4 in B, dropped out during the study. Comparison of group A with group B in WOMAC and pain (at rest and movement) scores showed insignificant difference at day 0 before prescription of the drugs. However comparison showed highly significant difference (P-value < 0.001) between the two groups in WOMAC, pain at rest and movement scores at the end of 6th and 12th weeks of intervention. Conclusion: Diacerein-Ginger is clinically more efficacious for management of knee OA than Diacerein alone
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".