Prevalence of major adverse cardiovascular events among Saudi patients with systemic lupus erythematosus compared with the general population: updates from the national SLE and PURE cohorts
Bibliographic record
Abstract
OBJECTIVE: This study examined the prevalence of major adverse cardiovascular events (MACE) among Saudi patients with SLE and the general population and considered factors associated with such outcomes were taken into consideration. METHODS: This is a cohort study evaluating the period prevalence of MACE from 2020 to 2023. The study used two datasets, namely the Saudi national prospective cohort for SLE patients and the Prospective Urban-Rural Epidemiology Study Saudi subcohort (PURE-Saudi) for the general population. Participants in both studies were monitored using a standardised protocol. MACE was defined as myocardial infarction (MI), stroke or angina. The analysis was adjusted for demographics, traditional cardiovascular risk factors and SLE diagnosis through logistic regression models. RESULTS: The PURE and national SLE cohorts comprised 488 and 746 patients, respectively. Patients with SLE from the SLE cohort were younger (40.7±12.5 vs 49.5±8.6 years) and predominantly female (90.6% vs 41.6%). The prevalence of traditional risk factors was greater in the PURE cohort compared with the SLE cohort. These factors included dyslipidaemia (28.9% vs 49.4%), obesity (63% vs 85%) and diabetes (7.8% vs 27.2%), but not hypertension (19.3% vs 18.8%). MACE (defined as MI or stroke or venous thromboembolism or heart failure) occurred more frequently in patients with SLE (4.3% vs 1.6%, p=0.004). Older age and lupus diagnosis were independently associated with MACE after adjusting for conventional risk factors. The odds of MACE were significantly related to age and lupus diagnosis (p=0.00 and p=0.00, respectively), but not cardiovascular disease (CVD) risk factors (p=0.83). CONCLUSION: Patients with SLE have a significantly higher risk of developing MACE than the general population. This risk is not well explained by traditional risk factors, which may explain the failure of CVD risk scores to stratify patients with SLE adequately. Further studies are needed to understand CVD risk's pathogenesis in SLE and mitigate it.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".