Risk of Myocardial Infarction and Stroke in Newly Diagnosed Systemic Lupus Erythematosus: A General Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: To estimate the future risk and time trends of newly diagnosed myocardial infarction (MI), ischemic stroke, or both (cardiovascular disease [CVD]) in individuals with systemic lupus erythematosus (SLE). METHODS: Using a population-based database that includes all residents of British Columbia, Canada, we conducted a matched cohort study of all patients with incident SLE and up to 10 age-, sex-, and entry time-matched individuals from the general population. We compared incidence rates (IRs) of MI, ischemic stroke, or CVD (i.e., MI or ischemic stroke) between the 2 groups according to SLE disease duration. We calculated hazard ratios (HRs), adjusting for confounders. RESULTS: Among 4,863 individuals with SLE (86% female, mean age 48.9 years), the IRs of MI, stroke, and CVD were 6.4, 4.4, and 9.9 events per 1,000 person-years, respectively, versus 2.8, 2.3, and 4.7 events per 1,000 person-years in the comparison cohort. Compared with non-SLE individuals, the fully adjusted multivariable HRs among SLE patients were 2.61 (95% confidence interval [95% CI] 2.12-3.20) for MI, 2.14 (95% CI 1.64-2.79) for stroke, and 2.28 (95% CI 1.90-2.73) for CVD. The age-, sex-, and entry time-matched HRs for MI, stroke, and CVD were highest during the first year after SLE diagnosis: 5.63 (95% CI 4.02-7.87), 6.47 (95% CI 4.42-9.47), and 6.28 (95% CI 4.83-8.17), respectively. CONCLUSION: Patients with SLE have an increased risk of cardiovascular events, particularly during the first year after diagnosis. Increased vigilance in monitoring for these potentially fatal outcomes and their modifiable risk factors is recommended in this patient population.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".