Revista Española de Cardiología (English Edition) Revista Española de Cardiología (English Edition)
Rev Esp Cardiol. 2007;60:693-702 - Vol. 60 Num.07 DOI: 10.1016/S1885-5857(08)60004-3

Estimating Cardiovascular Risk in Spain Using Different Algorithms

Eva Comín a, Pascual Solanas b, Carmen Cabezas c, Isaac Subirana d, Rafel Ramos e, Joan Gené-Badía f, Ferran Cordón g, María Grau e, Joan J Cabré-Vila h, Jaume Marrugat e

a Institut Català de la Salut, Barcelona, Spain
b Unitat Docent de Medicina de Familia de Girona, Institut Català de la Salut, Barcelona, Spain. Universitat Autònoma de Barcelona, Barcelona, Spain
c Fundació Gol i Gurina and Institut Català de la Salut, Barcelona, Spain
d Unitat de Lípids i Epidemiologia Cardiovascular, Institut Municipal d'Investigació Mèdica (IMIM), Barcelona, Spain
e Universitat Autònoma de Barcelona, Barcelona, Spain. Unitat de Lípids i Epidemiologia Cardiovascular, Institut Municipal d'Investigació Mèdica (IMIM), Barcelona, Spain
f Consorci d'Atenció Primària de l'Eixample, Universitat de Barcelona, Barcelona, Spain
g Unitat Docent de Medicina de Familia de Girona, Institut Català de la Salut, Barcelona, Spain
h EAP Reus-1, CAP Sant Pere, Barcelona, Spain

Keywords

Coronary disease. Risk factors. Hypercholesterolemia. Cardiovascular risk.

Abstract

Introduction and objectives. Although its incidence is low, cardiovascular disease is the most common cause of morbidity and mortality in Spain. A number of different algorithms can be used to calculate cardiovascular disease risk for primary prevention, but their ability to identify patients who will experience a cardiovascular event is not well understood. The objective of this study was to compare the results of using the original Framingham algorithm and two adaptations for low-risk countries: the REGICOR (Registre Gironí del cor) and SCORE (Systematic COronary Risk Evaluation) algorithms. Methods. All cardiovascular events during 5-year follow-up in a cohort of patients without coronary disease in nine autonomous Spanish regions were recorded. The levels of different cardiovascular risk factors were measured between 1995 and 1998. Participants were considered high-risk if their 10-year risk was ≥20% with the Framingham algorithm, ≥10%, ≥15% or ≥20% with REGICOR, and ≥5% with SCORE. Results. In total, 180 (3.1%) coronary events (112 in men and 68 in women) occurred among the 5732 (57.3% female) participants during follow-up. Of these, 43 died from cerebrovascular disease, and 24 had a non-coronary vascular event. The REGICOR algorithm had the highest positive predictive value for coronary and cardiovascular disease in all age groups. Moreover, with a 10-year risk limit of 10%, it classified less of the population aged 35-74 years as high-risk (i.e., 12.4%) than the Framingham algorithm (i.e., 22.4%). The SCORE and Framingham algorithms classified 8.4% and 16.6% of the population aged 35-64 years, respectively, as having a high cardiovascular disease risk; with REGICOR, the figure was 7.5%. Conclusions. The REGICOR adapted algorithm was the best predictor of cardiovascular events and classified a smaller proportion of the Spanish population aged 35-74 years as high risk than alternative algorithms.

1885-5857/© 2007 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved

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