The effect of a multidisciplinary lifestyle program for patients with rheumatoid arthritis, an increased risk for rheumatoid arthritis or with metabolic syndrome-associated osteoarthritis: the “Plants for Joints” randomized controlled trial protocol
Bibliographic record
Abstract
Abstract Low-grade inflammation and metabolic syndrome are seen in many chronic diseases, including rheumatoid arthritis (RA) and osteoarthritis (OA). Lifestyle interventions which combine different non-pharmacological therapies have shown synergizing effects in improving outcomes in patients with other chronic diseases or increased risk thereof, especially cardiovascular disease. For RA and metabolic syndrome-associated OA (MSOA), whole food plant-based diets (WFPDs) have shown promising results. A WFPD, however, had not yet been combined with other lifestyle interventions for RA and OA patients. In this protocol paper, we therefore present Plants for Joints, a multidisciplinary lifestyle program, based on a WFPD, exercise, and stress management. The objective is to study the effect of this program on disease activity in patients with RA (randomized controlled trial [RCT] 1), on a risk score for developing RA in patients with anti-citrullinated protein antibody (ACPA) positive arthralgia (RCT 2) and on pain, stiffness, and function in patients with MSOA (RCT 3), all in comparison with usual care. We designed three 16-week observer-blind RCTs with a waiting-list control group for patients with RA with low to moderate disease activity (2.6 ≤ Disease Activity Score [DAS28] ≤ 5.1, RCT 1, n = 80), for patients at risk for RA, defined by ACPA-positive arthralgia (RCT 2, n = 16) and for patients with metabolic syndrome and OA in the knee and/or hip (RCT 3, n = 80). After personal counseling on diet and exercise, participants join 10 group meetings with 6–12 other patients to receive theoretical and practical training on a WFPD, exercise, and stress management, while medication remains unchanged. The waiting-list control group receives usual care, while entering the program after the RCT. Primary outcomes are: difference in mean change between intervention and control groups within 16 weeks for the DAS28 in RA patients (RCT 1), the RA-risk score for ACPA positive arthralgia patients (RCT 2), and the Western Ontario and McMaster Universities Arthritis Index (WOMAC) score for MSOA patients (RCT 3). Continued adherence to the lifestyle program is measured in a two-year observational extension study.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".