Importance of cumulative exposure to elevated cholesterol and blood pressure in development of atherosclerotic coronary artery disease in systemic lupus erythematosus: a prospective proof-of-concept cohort study
Bibliographic record
Abstract
INTRODUCTION: Previous studies have shown that traditional risk factors such as hypercholesterolemia and hypertension account for only a small proportion of the dramatically increased risk of atherosclerotic coronary artery disease (CAD) in systemic lupus erythematosus (SLE). However, in these studies, exposure to risk factors was measured only at baseline. In this study, our objective was to compare measures of cumulative exposure with remote and recent values for each of total cholesterol (TC), systolic (SBP), and diastolic (DBP) blood pressure in terms of ability to quantify risk of atherosclerotic CAD in patients with SLE. METHODS: Patients in the Toronto lupus cohort had TC and BP measured at each clinic visit and were followed up prospectively for the occurrence of CAD. For each patient, arithmetic mean, time-adjusted mean (AM) and area-under-the-curve (AUC) were calculated for serial TC, SBP, and DBP measurements. Proportional hazards regression models were used to compare these summary measures with recent and first-available ("remote") measurements in terms of ability to quantify risk of CAD events, defined as myocardial infarction, angina, or sudden cardiac death. RESULTS: The 991 patients had a mean ± SD of 19 ± 19 TC measurements per patient. Over a follow-up of 6.7 ± 6.4 years, 86 CAD events occurred; although remote TC was not significantly predictive of CAD, mean and AM TC were more strongly predictive (hazard ratio (HR) 2.07; P = 0.003) than recent TC (HR 1.86, P = 0.001). AUC TC was not predictive of CAD. A similar pattern was seen for DBP and SBP. Older age, male sex, higher baseline and recent disease activity score, and corticosteroid use also increased CAD risk, whereas antimalarials were protective. CONCLUSIONS: In contrast to the population-based Framingham model, first-available TC and BP are not predictive of CAD among patients with SLE, in whom measures reflecting cumulative exposure over time are better able to quantify CAD risk. This is an important consideration in future studies of dynamic risk factors for CAD in a chronic relapsing-remitting disease such as SLE. Our findings also underpin the importance of adequate control of SLE disease activity while minimizing corticosteroid use, and highlight the cardioprotective effect of antimalarials.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".