Clinical associations of the metabolic syndrome in systemic lupus erythematosus: data from an international inception cohort
Bibliographic record
Abstract
BACKGROUND: The metabolic syndrome (MetS) may contribute to increased cardiovascular risk in systemic lupus erythematosus (SLE). We aimed to examine the association of demographic factors, lupus phenotype and therapy exposure with the presence of MetS. METHODS: The Systemic Lupus International Collaborating Clinics Registry for Atherosclerosis inception cohort enrolled recently diagnosed (<15 months) SLE patients from 30 centres across 11 countries from 2000. Clinical, laboratory and therapeutic data were collected according to a standardised protocol. MetS was defined according to the 2009 consensus statement from the International Diabetes Federation. Univariate and backward stepwise multivariate logistic regression were used to assess the relationship of individual variables with MetS. RESULTS: We studied 1686 patients, of whom 1494 (86.6%) had sufficient data to determine their MetS status. The mean (SD) age at enrolment and disease duration was 35.2 years (13.4) and 24.1 weeks (18.0), respectively. MetS was present at the enrolment visit in 239 (16%). In backward stepwise multivariable regression analysis, higher daily average prednisolone dose (mg) (OR 1.02, 95% CI 1.00 to 1.03), older age (years) (OR 1.04, 95% CI 1.03 to 1.06), Korean (OR 6.33, 95% CI 3.68 to 10.86) and Hispanic (OR 6.2, 95% CI 3.78 to 10.12) ethnicity, current renal disease (OR 1.79, 95% CI 1.14 to 2.80) and immunosuppressant use (OR 1.81, 95% CI 1.18 to 2.78) were associated with MetS. CONCLUSIONS: Renal lupus, higher corticosteroid doses, Korean and Hispanic ethnicity are associated with MetS in SLE patients. Balancing disease control and minimising corticosteroid exposure should therefore be at the forefront of personalised treatment decisions in SLE patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".