PT - JOURNAL ARTICLE AU - Johannes A N Dorresteijn AU - Frank L J Visseren AU - Annemarie M J Wassink AU - Martijn J A Gondrie AU - Ewout W Steyerberg AU - Paul M Ridker AU - Nancy R Cook AU - Yolanda van der Graaf AU - on behalf of the SMART Study Group TI - 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 AID - 10.1136/heartjnl-2013-303640 DP - 2013 Jun 15 TA - Heart PG - 866--872 VI - 99 IP - 12 4099 - http://heart.bmj.com/content/99/12/866.short 4100 - http://heart.bmj.com/content/99/12/866.full SO - Heart2013 Jun 15; 99 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.