Personalized diet and exercise recommendations in early rheumatoid arthritis: A feasibility trial
Bibliographic record
Abstract
BACKGROUND: Physical activity and diet have a positive influence on disease activity and cardiovascular risk in patients with rheumatoid arthritis (RA). OBJECTIVE: We tested the feasibility and effect of a brief individualized counselling intervention on physical activity levels and fitness, and dietary intake, compared with standard of care. METHODS: Thirty patients with inflammatory arthritis (<1 year duration) were assigned to standard of care or the intervention, which consisted of individualized visits with a dietetic intern and physiotherapist at two time points, to review age-specific strategies on diet and exercise. Primary outcomes included anthropometric measurements (height, weight, waist and hip circumference), nutritional intake, physical activity (pedometer steps) and physical fitness. Disease activity measures and biochemical testing (blood pressure measurement, inflammatory markers, cholesterol profile and random glucose) were collected. The changes in these outcomes from baseline to 6 months were assessed using paired t-tests between groups. RESULTS: Thirteen patients in the intervention group and 10 in the control group completed the study. There were non-significant trends in improvements in physical activity, low-density lipoprotein cholesterol level and nutritional intake (vitamin C, iron, fibre, vitamin A and folate) in the intervention group. CONCLUSIONS: Poor enrolment and high dropout rates in this short-term study highlighted the difficulty of behavioural change. Those continuing in the study and who received the intervention demonstrated a non-significantly improved activity level and nutritional intake that may benefit long-term outcomes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".