Physical activity and sedentary behavior in patients with systemic lupus erythematosus and rheumatoid arthritis
Bibliographic record
Abstract
Objective: Patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are at increased risk of cardiovascular disease (CVD). As sedentary behavior and lack of physical activity are known cardiovascular risk factors, we compared habitual activity between SLE patients, RA patients, and healthy control participants. Patients and methods: For this cross-sectional study, RA and SLE patients were recruited from rheumatology clinics at an academic medical center from April 2013 to December 2014. Healthy control participants were recruited through local advertising during the same time period. Habitual activity was measured using a triaxial accelerometer worn during waking hours for 7 consecutive days. Minutes per day of sedentary, light, and moderate–vigorous physical activity (MVPA) were recorded and compared between SLE, RA, and healthy participants using ANOVA. Results: There were 59 participants included in the analysis: 20 SLE patients, 19 RA patients, and 20 healthy controls. Disease activity was quiescent in both the SLE and RA groups. All three groups demonstrated high sedentary behavior (mean ± SD sedentary time for all participants: 10.1±1.3 hours/day; 76.4% total wear time). There were no significant differences between SLE, RA, and healthy participants in time spent in sedentary behavior ( p =0.80) or light activity ( p =0.17). Total MVPA (mean ± SD, minutes/day) was significantly lower in SLE (34.5±22.7; p <0.001) and RA (41.5±21.3; p =0.005) patients compared to controls (64.9±22.4). Conclusion: SLE and RA patients demonstrate suboptimal MVPA despite well-controlled disease. Given their increased CVD risk, effective interventions are required to improve habitual physical activity levels in both populations. Keywords: systemic lupus erythematosus, rheumatoid arthritis, physical activity, sedentary behavior, accelerometry
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".