Rafael Gabriel1, Carlos Brotons2, M José Tormo3, Antonio Segura4, Fernando Rigo5, Roberto Elosua6, Julio A Carbayo7, Diana Gavrila3, Irene Moral8, Jaakko Tuomilehto9, Javier Muñiz10. 1. Unidad de Epidemiología Clínica, Instituto IdiPAZ, Hospital Universitario La Paz, Universidad Autónoma de Madrid, Madrid, Spain; Red de Investigación Cardiovascular (RIC), Spain. Electronic address: rgabriel.hulp@salud.madrid.org. 2. Red de Investigación Cardiovascular (RIC), Spain; Unidad de Investigación, EAP Sardenya-IIB Sant Pau, Barcelona, Spain. 3. Servicio de Epidemiología, Conserjería de Sanidad de Murcia, Murcia, Spain; CIBER Epidemiología y Salud Pública, CIBERESP, Spain; Departamento de Ciencias Sociosanitarias, Universidad de Murcia, Murcia, Spain. 4. Instituto de Ciencias de la Salud de Castilla-La Mancha, Talavera de la Reina, Toledo, Spain. 5. Grupo CORSAIB, IB-Salut, Palma de Mallorca, Islas Baleares, Spain; Red de Investigación en Actividades Preventivas y Promoción de la Salud (redIAPP), Spain. 6. CIBER Epidemiología y Salud Pública, CIBERESP, Spain; Epidemiología Cardiovascular y Genética, IMIM (Instituto de Investigación Hospital del Mar), Barcelona, Spain. 7. Unidad de Lípidos, Clínica Nuestra Señora del Rosario, Grupo de Enfermedades Vasculares de Albacete (GEVA), Albacete, Spain. 8. Unidad de Investigación, EAP Sardenya-IIB Sant Pau, Barcelona, Spain. 9. Unidad de Epidemiología Clínica, Instituto IdiPAZ, Hospital Universitario La Paz, Universidad Autónoma de Madrid, Madrid, Spain; Red de Investigación Cardiovascular (RIC), Spain; University of Helsinki, Helsinki, Finland. 10. Unidad de Epidemiología Clínica, Instituto IdiPAZ, Hospital Universitario La Paz, Universidad Autónoma de Madrid, Madrid, Spain; Red de Investigación Cardiovascular (RIC), Spain; Instituto Universitario de Ciencias de la Salud, Universidad de A Coruña, A Coruña, Spain.
Abstract
INTRODUCTION AND OBJECTIVES: In Spain, data based on large population-based cohorts adequate to provide an accurate prediction of cardiovascular risk have been scarce. Thus, calibration of the EuroSCORE and Framingham scores has been proposed and done for our population. The aim was to develop a native risk prediction score to accurately estimate the individual cardiovascular risk in the Spanish population. METHODS: Seven Spanish population-based cohorts including middle-aged and elderly participants were assembled. There were 11800 people (6387 women) representing 107915 person-years of follow-up. A total of 1214 cardiovascular events were identified, of which 633 were fatal. Cox regression analyses were conducted to examine the contributions of the different variables to the 10-year total cardiovascular risk. RESULTS: Age was the strongest cardiovascular risk factor. High systolic blood pressure, diabetes mellitus and smoking were strong predictive factors. The contribution of serum total cholesterol was small. Antihypertensive treatment also had a significant impact on cardiovascular risk, greater in men than in women. The model showed a good discriminative power (C-statistic=0.789 in men and C=0.816 in women). Ten-year risk estimations are displayed graphically in risk charts separately for men and women. CONCLUSIONS: The ERICE is a new native cardiovascular risk score for the Spanish population derived from the background and contemporaneous risk of several Spanish cohorts. The ERICE score offers the direct and reliable estimation of total cardiovascular risk, taking in consideration the effect of diabetes mellitus and cardiovascular risk factor management. The ERICE score is a practical and useful tool for clinicians to estimate the total individual cardiovascular risk in Spain.
INTRODUCTION AND OBJECTIVES: In Spain, data based on large population-based cohorts adequate to provide an accurate prediction of cardiovascular risk have been scarce. Thus, calibration of the EuroSCORE and Framingham scores has been proposed and done for our population. The aim was to develop a native risk prediction score to accurately estimate the individual cardiovascular risk in the Spanish population. METHODS: Seven Spanish population-based cohorts including middle-aged and elderly participants were assembled. There were 11800 people (6387 women) representing 107915 person-years of follow-up. A total of 1214 cardiovascular events were identified, of which 633 were fatal. Cox regression analyses were conducted to examine the contributions of the different variables to the 10-year total cardiovascular risk. RESULTS: Age was the strongest cardiovascular risk factor. High systolic blood pressure, diabetes mellitus and smoking were strong predictive factors. The contribution of serum total cholesterol was small. Antihypertensive treatment also had a significant impact on cardiovascular risk, greater in men than in women. The model showed a good discriminative power (C-statistic=0.789 in men and C=0.816 in women). Ten-year risk estimations are displayed graphically in risk charts separately for men and women. CONCLUSIONS: The ERICE is a new native cardiovascular risk score for the Spanish population derived from the background and contemporaneous risk of several Spanish cohorts. The ERICE score offers the direct and reliable estimation of total cardiovascular risk, taking in consideration the effect of diabetes mellitus and cardiovascular risk factor management. The ERICE score is a practical and useful tool for clinicians to estimate the total individual cardiovascular risk in Spain.
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