MO267: Traditional and Disease-Related Cardiovascular Risk Factors in Anca-Associated Vasculitis: A Prospective, Two-Centre, Observational Cohort Study
Bibliographic record
Abstract
Abstract BACKGROUND AND AIMS ANCA-associated vasculitis (AAV) has been associated with increased risk of cardiovascular (CV) events. The purpose of the present study was to asses cardiovascular risk determinants and outcomes in a two-centre prospective cohort of AAV patients. METHOD Prevalent patients diagnosed with AAV ≥ 3 months were recruited over a period of 8 months from the Northwest Clinics in the Netherlands and 3 months from the Mount Sinai Hospital in Canada, and followed for 3–5 years. A comprehensive CV risk assessment was performed at inclusion. Subjects were followed up yearly until the first cardiovascular event, death or end of follow-up, whichever came first. Cardiovascular events were assessed by an independent outcome panel. Cox proportional hazards analyses were performed to relate baseline characteristics to the first CV event. RESULTS A total of 144 patients were included (median age 64.6 years, male sex 56%, median BVAS score 0, median Framingham risk score 14.3%). After a median follow-up of 2.91 years, 28 non-fatal and 4 fatal CV events were registered in 16 patients. Twelve patients died of non-cardiovascular causes. The incidence of fatal and non-fatal CV events was 5.5 per 100 patient-years. In a univariable analysis an association was found between traditional risk factors and risk of CV events [hazard ratio (HR) (95% confidence interval)], including age [HR 1.08 (95% CI 1.03–1.14)], HbA1c [HR 1.59 (95% CI 1.15–2.22)], systolic blood pressure [HR 1.04, 1.01–1.06), history of CV event [HR 3.47 (95% CI 1.29–9.32)] and Framingham risk score [HR 1.05 (95% CI 1.03–1.08)]. After adjusting for age and sex, HbA1c [HR 1.70 (95% CI 1.17–2.48)] and previous CV event [HR 2.90 (95% CI 1.02–8.21)] remained significantly associated with CV events. In a multivariable cox regression analysis (adjusted for Framingham risk score), a longer disease duration was associated with CV events [HR 1.08 (95% CI 1.01–1.16)]. CONCLUSION The present study is the largest prospective study on CV risk in patients with AAV and showed that CV risk was driven by both traditional and disease-related risk factors. Disease duration is associated with increased risk of CVE, but which precise disease-related factors accounts for this finding, and whether it can be acted upon remain to be determined.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".