Effects of adding vitamin B to Diclofenac on knee osteoarthritis pains
Bibliographic record
Abstract
Background: Knee osteoarthritis is one of the most prevalent chronic disorders. Several pharmacological and non-pharmacological approaches have been used to treat knee osteoarthritis. Objective: The aim of this study was to determine the effects of adding vitamin B to Diclofenac on pain due to knee osteoarthritis. Methods: This double-blind clinical trial was carried out on 73 patients with knee osteoarthritis referred to the Rheumatology and Orthopedics clinics of Shahrekord University of Medical sciences in 2013. The patients underwent treatment with oral Diclofenac plus oral vitamin B (38 patients), or oral Diclofenac plus placebo (35 patients). Pain was measured by the visual analogue scale (VAS) and morning stiffness and physical functioning were measured by the Western Ontario and McMaster Universities Arthritis Index (WOMAC) before treatment, and 14 and 21 days after treatment. Data were analyzed using Chi-square test, T-test, and repeated measures ANOVA. Findings: The visual analogue WOMAC mean score for knee pain, overall pain severity, stiffness of knee joint, and function in the last 48 hours significantly decreased in both groups from the first to third measurement. Decrease in overall pain severity, function in the last 48 hours and stiffness of knee joint scores in vitamin B group was more than Diclofenac group. Decrease in knee pain VAS was similar in both groups. Patient satisfaction was not significantly different between the two groups. Conclusion: With regards to the results, it seems that vitamin B supplement is useful for the treatment of osteoarthritis symptoms.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".