[Estimating cardiovascular risk in Spain using different algorithms]

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 >or=20% with the Framingham algorithm, >or=10%, >or=15% or >or=20% with REGICOR, and >or=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.