Comparative effectiveness of a complex Ayurvedic treatment and conventional standard care in osteoarthritis of the knee – study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Traditional Indian Ayurvedic medicine uses complex treatment approaches, including manual therapies, lifestyle and nutritional advice, dietary supplements, medication, yoga, and purification techniques. Ayurvedic strategies are often used to treat osteoarthritis (OA) of the knee; however, no systematic data are available on their effectiveness in comparison with standard care. The aim of this study is to evaluate the effectiveness of complex Ayurvedic treatment in comparison with conventional methods of treating OA symptoms in patients with knee osteoarthritis. METHODS AND DESIGN: In a prospective, multicenter, randomized controlled trial, 150 patients between 40 and 70 years, diagnosed with osteoarthritis of the knee, following American College of Rheumatology criteria and an average pain intensity of ≥40 mm on a 100 mm visual analog scale in the affected knee at baseline will be randomized into two groups. In the Ayurveda group, treatment will include tailored combinations of manual treatments, massages, dietary and lifestyle advice, consideration of selected foods, nutritional supplements, yoga posture advice, and knee massage. Patients in the conventional group will receive self-care advice, pain medication, weight-loss advice (if overweight), and physiotherapy following current international guidelines. Both groups will receive 15 treatment sessions over 12 weeks. Outcomes will be evaluated after 6 and 12 weeks and 6 and 12 months. The primary endpoint is a change in the score on the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) after 12 weeks. Secondary outcome measurements will use WOMAC subscales, a pain disability index, a visual analog scale for pain and sleep quality, a pain experience scale, a quality-of-life index, a profile of mood states, and Likert scales for patient satisfaction, patient diaries, and safety. Using an adapted PRECIS scale, the trial was identified as lying mainly in the middle of the efficacy-effectiveness continuum. DISCUSSION: This trial is the first to compare the effectiveness of a complex Ayurvedic intervention with a complex conventional intervention in a Western medical setting in patients with knee osteoarthritis. During the trial design, aspects of efficacy and effectiveness were discussed. The resulting design is a compromise between rigor and pragmatism. TRIAL REGISTRATION: NCT01225133.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".