Association of cardiovascular health and risk prediction algorithms with subclinical atherosclerosis identified by carotid ultrasound.

Background: The requirement for laboratory tests to assess conventional cardiovascular disease (CVD) risk may be a barrier to the early detection and management of atherosclerosis in some population groups. A simpler risk assessment could facilitate detection of CVD. Objectives: The association of the Fuster-BEWAT Score (FBS), Framingham Risk Score (FRS), and Pooled Cohort Equation (PCE) with the presence of carotid plaque was investigated, with the intention of developing a stepped screening process for the primary prevention of CVD. Methods: Asymptomatic participants with a family history of premature CVD had an absolute cardiovascular disease risk (ACVDR) score calculated using the FBS, FRS, and PCE risk equations. This risk classification was compared with the presence or absence of carotid plaque on ultrasound. Prediction of carotid plaque presence by risk scores and risk factors was assessed by logistic regression and area under the curve (AUC) for discrimination and diagnostic performance. A classification and regression-tree (CART) model was obtained for stratification of risk assessment. Results: Risk score calculation and ultrasound scanning were performed in 1031 participants, of whom 51 had carotid plaques. Participants with plaque and male sex showed higher risk (higher PCE and FRS and lower FBS, as higher scores of FBS indicate better cardiovascular health). Participants ≤50 years of age showed the FBS was a significant predictor; there was a reduced likelihood of plaque presence with a higher score (OR 0.54, 95% CI 0.39-0.75, Conclusion: FBS was able to identify the presence of carotid plaque in asymptomatic individuals. Its use for initial risk delineation might improve the selection of patients for more specific and complex assessment, reducing cost and time.