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.
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.
Authors: Vicente Gil-Guillen; Domingo Orozco-Beltran; Josep Redon; Salvador Pita-Fernandez; Jorge Navarro-Pérez; Vicente Pallares; Francisco Valls; Carlos Fluixa; Antonio Fernandez; Jose M Martin-Moreno; Manuel Pascual-de-la-Torre; Jose L Trillo; Ramon Durazo-Arvizu; Richard Cooper; Marta Hermenegildo; Luis Rosado Journal: BMC Public Health Date: 2010-11-22 Impact factor: 3.295
Authors: Johanna A Damen; Romin Pajouheshnia; Pauline Heus; Karel G M Moons; Johannes B Reitsma; Rob J P M Scholten; Lotty Hooft; Thomas P A Debray Journal: BMC Med Date: 2019-06-13 Impact factor: 8.775
Authors: Carmen Gómez-Vaquero; Alfonso Corrales; Andrea Zacarías; Javier Rueda-Gotor; Ricardo Blanco; Carlos González-Juanatey; Javier Llorca; Miguel A González-Gay Journal: Arthritis Res Ther Date: 2013-08-21 Impact factor: 5.156
Authors: Domingo Orozco-Beltran; Jose A Quesada; Vicente Bertomeu-Gonzalez; Jose M Lobos-Bejarano; Jorge Navarro-Perez; Vicente F Gil-Guillen; Luis Garcia Ortiz; Adriana Lopez-Pineda; Angel Castellanos-Rodriguez; Angela Lopez-Domenech; Antonio Francisco J Cardona-Llorens; Concepcion Carratala-Munuera Journal: Sci Rep Date: 2020-03-16 Impact factor: 4.379
Authors: Arantxa Catalán-Ramos; Jose M Verdú; María Grau; Manuel Iglesias-Rodal; José L del Val García; Alicia Consola; Eva Comin Journal: Aten Primaria Date: 2013-12-09 Impact factor: 1.137