Objective: Coronary heart diseases (CHD) are the leading cause of premature death and loss of disability adjusted life years in Europe. In order to implement appropriate health interventions as preventive tools, it is necessary to understand the epidemiological stratification of cardiovascular risk and the specific situation of each individual reality. This study investigates the reliability of two algorithms used to assess cardiovascular risk: the Framingham algorithm and the CUORE algorithm.
Patients and methods: Data specific on patients of General Practitioners working in the Province of Rome were considered, and a total of 996 subjects of both genders were evaluated. The goodness of fit of the regression model was evaluated using the R2 value.
Results: The inferential analysis showed that the R2 value of the simple linear regression between CHD risk calculated according to the CUORE method (dependent variable) and CHD risk calculated according the Framingham method (independent variable), was initially equal to 0.350, and rose to 0.732 when the independent variables "Gender" and "Age" were added, thereby creating a multivariate regression. The R2 of the multivariate regression was 0.478 when using CHD Framingham as the dependent variable and CHD CUORE as the independent variable.
Conclusions: It emerged that the CUORE score was less reliable than the Framingham risk score; in fact, in the multiple linear regression model, the coefficient of determination was greater when the independent variable was the Framingham scale for CHD risk.