A Novel Model for Prediction of Thromboembolic and Cardiovascular Events in Patients Without Atrial Fibrillation
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abstract
Patients without atrial fibrillation (AF) constitute approximately 75% of patients suffering thromboembolism and major adverse cardiovascular events (MACE), but evidence supporting risk stratification in these patients is sparse. We aimed to develop a risk prediction model for identification of patients without AF at high risk of first-time thromboembolic events. We included 72,381 coronary angiography patients without AF and without previous ischemic stroke or transient ischemic attack. The cohort was randomly divided into a derivation cohort (80%, n = 57,680) and a validation cohort (20%, n = 14,701). The primary thromboembolic end point was a composite of ischemic stroke, transient ischemic attack, and systemic embolism. MACE was defined as a composite of cardiac death, myocardial infarction, and ischemic stroke. The final model was compared with 2 validated clinical risk models (CHADS2 and CHA2DS2-VASc). The risk prediction model assigned 1 point to heart failure, hypertension, diabetes mellitus, renal disease, age 65 to 74 years, active smoking, and multivessel obstructive coronary artery disease, and 2 points to age ≥75 years and peripheral artery disease. A C-index of 0.66 (95% CI 0.64 to 0.69) for prediction of the composite thromboembolic end point was found in the validation cohort, which was higher than for CHADS2 (C-index 0.63 [95% CI 0.60 to 0.67]; p < 0.001) and CHA2DS2-VASc (C-index 0.64 [95% CI 0.62 to 0.67]; p = 0.034). The model also predicted MACE (C-index 0.71 [95% CI 0.69 to 0.73]). In conclusion it is possible to identify patients without AF at high risk of first-time thromboembolic events and MACE by use of a simple clinical prediction model.
