RT Journal Article SR Electronic T1 Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score JF Heart JO Heart FD BMJ Publishing Group Ltd and British Cardiovascular Society SP 866 OP 872 DO 10.1136/heartjnl-2013-303640 VO 99 IS 12 A1 Johannes A N Dorresteijn A1 Frank L J Visseren A1 Annemarie M J Wassink A1 Martijn J A Gondrie A1 Ewout W Steyerberg A1 Paul M Ridker A1 Nancy R Cook A1 Yolanda van der Graaf A1 on behalf of the SMART Study Group YR 2013 UL http://heart.bmj.com/content/99/12/866.abstract AB Objectives To enable risk stratification of patients with various types of arterial disease by the development and validation of models for prediction of recurrent vascular event risk based on vascular risk factors, imaging or both. Design Prospective cohort study. Setting University Medical Centre. Patients 5788 patients referred with various clinical manifestations of arterial disease between January 1996 and February 2010. Main outcome measures 788 recurrent vascular events (ie, myocardial infarction, stroke or vascular death) that were observed during 4.7 (IQR 2.3 to 7.7) years’ follow-up. Results Three Cox proportional hazards models for prediction of 10-year recurrent vascular event risk were developed based on age and sex in addition to clinical parameters (model A), carotid ultrasound findings (model B) or both (model C). Clinical parameters were medical history, current smoking, systolic blood pressure and laboratory biomarkers. In a separate part of the dataset, the concordance statistic of model A was 0.68 (95% CI 0.64 to 0.71), compared to 0.64 (0.61 to 0.68) for model B and 0.68 (0.65 to 0.72) for model C. Goodness-of-fit and calibration of model A were adequate, also in separate subgroups of patients having coronary, cerebrovascular, peripheral artery or aneurysmal disease. Model A predicted <20% risk in 59% of patients, 20–30% risk in 19% and >30% risk in 23%. Conclusions Patients at high risk for recurrent vascular events can be identified based on readily available clinical characteristics.