Association between physical activity and subsequent changes in disease activity in people living with rheumatoid arthritis
Bibliographic record
Abstract
Various studies have demonstrated how rheumatoid arthritis (RA) patients perform less physical activity than the general population, likely due to joint pain and impaired physical function. However, physical activity (PA) may have beneficial effects on reducing inflammation and RA disease activity. The objective of this study was to evaluate the association between baseline PA levels and self-reported changes in measures of RA disease activity. We conducted a longitudinal study using 2015-2017 data from an annual survey administered to an RA cohort in BC. Subjects were grouped into three levels (Low, Medium and High) of PA at the baseline year (2015) according to the specifications of the International Physical Activity Questionnaire. Subsequently, we examined whether baseline PA was associated with changes in RA disease activity outcomes over 2015 to 2017, using fitted linear mixed models for each measure and adjusting for age, sex and other covariates. Of the 169 patients who responded to the 2015 survey, 29.6%, 42.0%, and 28.4% were grouped into Low, Medium, and High levels of PA, respectively. Our results demonstrated that the Low PA group experienced significant worsening of disease activity outcomes over the three years, including those of the Rheumatoid Arthritis Disease Activity Index (RADAI) (p=0.007), Fatigue (p=0.007), and Pain (p=0.007). Those in the Medium and High PA groups at baseline experienced either a decrease or no change in their disease activity outcomes over time. These results add to the accumulating evidence that physical activity may reduce disease activity and is essential to RA management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".