Recent corticosteroid use and recent disease activity: Independent determinants of coronary heart disease risk factors in systemic lupus erythematosus?
Bibliographic record
Abstract
OBJECTIVE: Systemic lupus erythematosus (SLE) is characterized by a markedly elevated risk for coronary heart disease (CHD), the exact pathogenesis of which is unknown. In particular, the causal roles of corticosteroid therapy and SLE disease activity, and whether their putative effects are mediated through conventional risk factors, remain unclear. METHODS: Data abstracted retrospectively from the charts at 11,359 clinic visits for 310 patients with SLE to the Montreal General Hospital were used to investigate the associations of recent corticosteroid dose and recent Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score with 8 CHD risk factors (total serum cholesterol, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein cholesterol, apolipoprotein B [Apo B], triglycerides, systolic blood pressure [BP], body mass index, and blood glucose) and the aggregate estimate of 2-year CHD risk. Separate multivariable linear regression models estimated the mutually-adjusted effects of average daily corticosteroid dose and average SLEDAI score within the past year on the current level of each risk factor while adjusting for age, sex, cumulative damage score, disease duration, and, where appropriate, use of relevant medications. RESULTS: Higher past-year corticosteroid dose was independently associated with significantly higher overall 2-year CHD risk and with higher levels of all 8 individual risk factors. Higher past-year lupus disease activity was independently associated with higher overall 2-year CHD risk, lower HDL cholesterol, and higher values of systolic BP, Apo B, triglycerides, and blood glucose. CONCLUSION: In SLE, both recent use of corticosteroids and recent lupus activity are independently associated with higher values of several well-recognized CHD risk factors and overall 2-year CHD risk.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".