Study of oral glucosamine, methylsulfonylmethane and their combination in osteoarthritis of the knee
Bibliographic record
Abstract
Background: Osteoarthritis (OA) of the knee is the most common degenerative joint disorder that results in disability and increased morbidity. Conventional treatment of OA with non-steroidal anti-inflammatory drugs (NSAIDs) often leads to serious adverse side effects that may increase morbidity and mortality. Glucosamine and Methylsulfonylmethane (MSM) have anti-inflammatory and analgesic properties which may supplement NSAIDs. Hence this study was aimed to determine the effectiveness and safety of these drugs in the management of knee OAMethods: 76 (63.33%) female and 44 (36.67%) male patients of OA of the knees were divided equally into four groups depending upon the therapy with Glucosamine or MSM or their combination (study groups) or none of them (control group) for 12 weeks. After the written consent, a detail Clinical History& Examination, Biochemical investigations, X-rays of chest and knees and ECG were done. The outcome of the treatment was assessed by Western Ontario and McMaster University Osteoarthritis (WOMAC) Index and for any adverse drug effects.Results: After 12 weeks of study there was significant decrease in mean WOMAC pain scores (27.29-39.13) and total aggregate scores (23.53-37.14%) in study groups (p<0.01-p<0.001) as compared to control group (14.28 % and 8.82% respectively). Besides the relief of pain and improvement in physical functions were superior in patients treated with combination therapy. Conclusions: This study showed Glucosamine & MSM are effective in the management of OA of knee and are safe health supplement to NSAIDs while their combination was more superior and effective.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".