Estimación de riesgo de enfermedad coronaria mediante la función de Framingham adaptada para la población chilena

• Gloria lcaza ^[1] ; Loreto Núñez ^[1] ; Jaume Marrugat ^[3] ; Verónica Mujica ^[1] ; M. Cristina Escobar ^[2] ; Ana Luisa Jiménez ^[4] ; Paulina Pérez ; Iván Palomo ^[1]
  1. [1] Universidad de Talca

     Universidad de Talca

     Provincia de Talca, Chile

     
  2. [2] Ministerio de Salud

     Ministerio de Salud

     Perú

     
  3. [3] Institut Municipal d'Investigació Medica Programa de Recerca en Processos Inflamatoris i Cardiovasculars Unitat de Lípids i Epidemiología Cardiovascular
  4. [4] Centro de Salud Astaburuaga

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• Localización: Revista Médica de Chile, ISSN-e 0034-9887, Vol. 137, Nº. 10, 2009, págs. 1273-1282
• Idioma: español
• Títulos paralelos:
  • Estimation of coronary heart disease risk in Chilean subjects based on adapted Framingham equations
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• Resumen

  • Background: Cardiovascular disease is the leading cause of morbidity and mortality in Chile and worldwide. Framingham functions were developed to calculate overall coronary heart disease risk However these functions overestimate the risk in some countries ¡ike Chile. Aim To develop Chilean risk tables to assess the overall 10-year risk of coronary heart disease. Material and methods: The Framingham function was adapted for a population aged 35 to 74 years, based on an estimate of Chilean incidence of coronary heart disease and the prevalence of coronary heart disease risk factors such as age, sex, total cholesterol, high-density lipoprotein cholesterol, blood pressure, diabetes and smoking. Results: The 10-year incidence of coronary heart disease in Chile (2.7% in men, 1.096 in women) was lower than the incidence in the United States (10.096/3.896) and Spain (4.996/2.296), but higher than China (1.196/0.496). Framingham tables have more than 50% of cells in the risk category of 10% or greater. In contrast, Chilean tables have less than 10% of cells in the same risk category. Conclusions: Adapted tables use local information to calculate overall coronary heart disease risk. A validation study should be conducted to assess their predictive power.