Physical activity, sedentary behaviour and their associations with cardiovascular risk in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: Using a novel isotemporal substitution paradigm, this study aimed to estimate the cross-sectional associations of objectively measured sedentary behaviour and physical activity (PA) with cardiovascular risk factors among patients with SLE. METHODS: This was a cross-sectional study of adult SLE patients without documented cardiovascular disease (CVD). Cardiovascular risk factors were measured, including BMI, blood pressure, fasting glucose and lipid profile. Ten-year CVD risk was estimated using the American College of Cardiology/American Heart Association risk assessment tool. Time in sedentary behaviour, light PA, and moderate-vigorous PA (MVPA) was measured by accelerometry. We used three linear regression models-single-activity models, partition models, and isotemporal substitution models-to evaluate the associations of time spent at each movement intensity with each CVD risk variable. RESULTS: There were 100 SLE patients [92% female; mean (s.d.) age 52.4 (14.4) years]. Only 11 participants adhered to current PA recommendations (⩾150 MVPA min/week in ⩾10-min bouts). In isotemporal substitution, reallocating 10 min from sedentary behaviour to MVPA was associated with lower systolic (β = -2.15 mmHg; P = 0.01) and diastolic blood pressure (β = -1.56 mmHg; P = 0.01), as well as lower estimated 10-year CVD risk (RR 0.81, 95% CI 0.70, 0.93). Time reallocation from light PA to MVPA was associated with lower diastolic blood pressure (β = -1.45 mmHg; P = 0.01) and lower 10-year CVD risk estimates (RR 0.80, 95% CI 0.69, 0.94). CONCLUSION: Given that reallocating time from other movement intensities to MVPA is associated favourably with lower cardiovascular risk, PA interventions are needed to address suboptimal MVPA levels among SLE patients.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".