Comparative effectiveness of Ayurveda treatment and conventional care in knee osteoarthritis
Bibliographic record
Abstract
Osteoarthritis (OA) is of global relevance with up to 250 million people affected by knee OA [Michaud 2006; OARSI 2016; Bitton 2009; Abramson 2009]. Despite progress in conventional care, patients continue to be affected by disability, and there is a need for further treatment approaches [McAlindon 2014; Hochberg 2012; Griffin 1991]. In South Asia, Ayurveda is commonly used as a treatment approach in knee OA. Ayurveda uses individualized treatments with a multi-modal concept utilizing manual and nutritional therapy, herbal therapy, lifestyle counseling and yoga [Tuffs 2002]. No clinical trial evaluated Ayurveda treatment with such an approach for knee OA prior to this study [Lauche 2016]. The goal was to analyze clinical effectiveness of an Ayurvedic method by example of treatments on patients with knee OA. In this case, a comparison was made of the treatment methods Ayurveda and conventional therapy of knee OA. For this purpose, patients diagnosed with knee OA according to ACR (American College of Rheuma-tology) criteria were included in a "multicenter, randomized, control¬led clinical trial". Of 151 enrolled patients, 77 received Ayurveda therapy and the remaining 74 were treated by conventional therapy. Every participant received 15 treatments during a period of 12 weeks. The primary outcome was the change on the Western Ontario and McMaster University Osteoarthritis (WOMAC) Index according to the validated German version after 12 weeks. Parameters for the secondary outcome consisted of WOMAC subscales (pain, stiffness, function); validated questionnaires for pain, pain experience, quality of life and mood; numeric rating scales for pain and sleep quality; rescue medication use and safety issues. [Kessler 2018] In summary, the improvements shown in the WOMAC Index from baseline to 12 weeks were greater in the “Ayurveda group (mean difference 61.0 [95 % CI: 52.4;69.6]) than in the conventional group (32.0 [95 % CI: 21.4;42.6])”. Moreover, this result was under-lined with a significant between-group “difference (p<0.001) and a clinically relevant effect size (Cohen’s d 0.68 [95 % CI:0.35;1.01])”. After 12 weeks of treatment, com-parable effects in favor of Ayurveda were detected for a number of secondary outcomes. Furthermore, even 3 and 9 months after the last treatments therapy effects persisted. These findings imply that the treatment of knee OA with a complex Ayurvedic therapy might be superior to a complex conventional OA therapy. However, additional studies are required to examine the extent of the effectiveness and to illuminate further the influence of diverse treatment factors and "non-specific effects". [Kessler 2018]
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".