A Randomised Placebo-Controlled Clinical Trial of Homeopathic Medicines on Osteoarthritis
Bibliographic record
Abstract
Abstract Background Osteoarthritis (OA) is one of the most common musculoskeletal disorders present worldwide. It increases with age and is prevalent among elderly people affecting their daily activities thus adding to the economic burden. Objectives This clinical study was undertaken to assess the efficacy of homeopathic medicines in the treatment of OA. Methods This single-blind, randomised, placebo-controlled, clinical trial was conducted on 90 patients suffering from OA. Each patient was randomised into an intervention group (IG) and a control group (CG). The IG (n = 60) received individualised homeopathic medicine (IHM) based on the symptom similarity of the case. The CG (n = 30) received an identical-looking placebo. Outcome assessment was done by assessing the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores at the baseline and after 3 months of follow-up. Paired t-test was used to determine differences between before and after treatment within groups. Results The difference in the WOMAC index score before and after treatment in the CG was found non-significant (p = 0.96), while in the IG the difference was statistically significant (p < 0.05) at a 95% of confidence level. The most useful medicines indicated were Bryonia alba, Medorrhinum, Pulsatilla pratensis, Rhus toxicodendron, Arnica montana, Causticum and Sulphur. Conclusion Patients with OA reported a significant decrease in WOMAC index score after 3 months of homeopathic treatment based on the totality of 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".