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. Issue 12 (10th April 2013)

• Record Type: Journal Article
• Authors: Dorresteijn, Johannes A N; Visseren, Frank L J; Wassink, Annemarie M J; Gondrie, Martijn J A; Steyerberg, Ewout W; Ridker, Paul M; Cook, Nancy R; van der Graaf, Yolanda
• Other Names: Algra A author non-byline.; Grobbee DE author non-byline.; Rutten GEHM author non-byline.; Moll FL author non-byline.; Kappelle LJ author non-byline.; Mali WPTM author non-byline.; Doevendans PA author non-byline.
• Is Part Of: Heart. Volume 99:Issue 12(2013)
• Page Start: 866
• Page End: 872
• Publication Date: 2013-04-10
• Subjects: Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2013-303640
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : 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.