Following a recent study in cardiovascular disease (CVD) risk assessment, the American Heart Association (AHA) has introduced the Predicting Risk of CVD EVENTs (PREVENT) equations. This new development addresses the limitations of existing multivariable equations by providing a meticulously developed and validated tool designed for US adults aged 30 to 79 without known CVD.
Alan S. Go, MD, Kaiser Permanente School of Medicine (KPSOM) Professor of Health Systems Science, coauthored the study, titled “Development and Validation of the American Heart Association Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) Equations,” which was recently published in the AHA medical journal, Circulation.
The PREVENT equations incorporate traditional risk factors and additional predictors, such as estimated urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index. Spanning 25 datasets and 6,612,004 adults, the equations demonstrated remarkable accuracy and precision in predicting incident CVD and its subtypes. Sex-specific, race-free, and adjusted for non-CVD death risks, these equations boast unprecedented accuracy and precision.