Factors Associated with Major Cardiovascular Events in Patients with Systemic Necrotizing Vasculitides: Results of a Longterm Followup Study
Bibliographic record
Abstract
OBJECTIVE: Systemic necrotizing vasculitides (SNV) are associated with more frequent subclinical atherosclerosis, suggesting that SNV might be associated with a higher risk of major cardiovascular events (MCVE). We aimed to identify factors predictive of MCVE in patients with SNV. METHODS: Patients in remission from SNV were assessed for CV risk factors and subclinical atherosclerosis. MCVE was defined as myocardial infarction, stroke, arterial revascularization, hospitalization for unstable angina, and/or death from CV causes. MCVE-free survival curves were compared using the log-rank test. RESULTS: Forty-two patients were followed for 7.1±2.6 years. Eight patients (18.9%) had MCVE. The respective 5- and 10-year MCVE rates were 9.5% and 26.8%. National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III)-defined high-risk status [hazard ratio (HR) 5.02 (95% CI: 1.17-27.4), p=0.03], BMI>30 kg/m2 [HR 4.84 (95% CI: 1.46-116), p=0.02], and plaque detection in the abdominal aorta (p=0.01) were significantly associated with MCVE. SNV characteristics, corticosteroid maintenance therapy, and C-reactive protein>5 mg/l were not associated with MCVE. Plaque in the aorta was significantly associated with high-risk status (p<0.001), while BMI and high-risk status were independent variables. Thus, a BMI>30 kg/m2 and/or a high-risk status were strongly associated with MCVE (p=0.004). Carotid intima-media thickness (IMT) identified patients with early MCVE and was correlated with the time to MCVE (r2=0.68, p=0.01). CONCLUSION: These results suggest that factors associated with a higher MCVE risk in patients with SNV are NCEP/ATP III-defined high-risk status and BMI>30 kg/m2. Carotid IMT could help identify patients with SNV at risk of early MCVE.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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".