Degree of Agreement between Cardiovascular Risk Stratification Tools

• Autor(a) principal: Garcia,Guilherme Thomé
• Data de Publicação: 2017
• Outros Autores: Stamm,Ana Maria Nunes de Faria, Rosa,Ariel Córdova, Marasciulo,Antônio Carlos, Marasciulo,Rodrigo Conill, Battistella,Cristian, Remor,Alexandre Augusto de Costa
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Arquivos Brasileiros de Cardiologia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2017000500427
• topic: Cardiovascular Diseases / mortality; Cardiovascular Diseases / morbidity; Risk Assessment; Cardiovascular Diseases / epidemiology; Period Analysis

Abstract Background: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in Brazil, and primary prevention care may be guided by risk stratification tools. The Framingham (FRS) and QRISK-2 (QRS) risk scores estimate 10-year overall cardiovascular risk in asymptomatic individuals, but the instrument of choice may lead to different therapeutic strategies. Objective: To evaluate the degree of agreement between FRS and QRS in 10-year overall cardiovascular risk stratification in disease-free individuals. Methods: Cross-sectional, observational, descriptive and analytical study in a convenience sample of 74 individuals attending the outpatient care service of a university hospital in Brazil between January 2014 and January 2015. After application of FRS and QRS, patients were classified in low/moderate risk (< 20%) or high risk (≥ 20%). Results: The proportion of individuals classified as at high risk was higher in FRS than in QRS (33.7% vs 21.6%). A synergic effect of male gender with systemic arterial hypertension was observed in both tools, and with for geriatric age group in QRS (p < 0.05) in high-risk stratum. The Kappa index was 0.519 (95%CI = 0.386-0.652; p < 0.001) between both instruments. Conclusion: There was a moderate agreement between FRS and QRS in estimating 10-year overall cardiovascular risk. The risk scores used in this study can identify synergism between variables, and their behavior is influenced by the population in which it was derived. It is important to recognize the need for calibrating risk scores for the Brazilian population.