PREVENT equations developed and validated in adults aged 30 to 79 years without known CVD and included eGFR as a predictor
MONDAY, Nov. 13, 2023 (HealthDay News) — The Predicting Risk of Cardiovascular Disease (CVD) Events (PREVENT) risk calculator estimates the risk for CVD, including heart failure, according to a methods paper and accompanying scientific statement published online Nov. 10 in Circulation to coincide with the American Heart Association Scientific Sessions 2023, held from Nov. 11 to 13 in Philadelphia.
Sadiya S. Khan, M.D., from the Northwestern University Feinberg School of Medicine in Chicago, and colleagues developed and validated the PREVENT equations among U.S. adults aged 30 to 79 years without known CVD. The derivation sample included individual-level participant data from 25 datasets with 3,281,919 participants; external validation was performed in 3,330,085 participants from 21 additional datasets. Predictors included traditional risk factors and estimated glomerular filtration rate (eGFR). The researchers identified 211,515 incident total CVD events during a mean follow-up of 4.8 years. In external validation for CVD, the median C-statistics were 0.794 and 0.757 in female and male participants, respectively. For men and women, the calibration curves were 1.03 and 0.94, respectively. Similar estimates for discrimination and calibration were seen for atherosclerotic CVD- and heart failure-specific models.
In a scientific statement, Khan and colleagues discuss the clinical implications of the PREVENT equations. The authors note that use of the equations allows 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure). The sex-specific risk equations include eGFR as a predictor and remove race from risk prediction estimates.
“The PREVENT equations are a critical first step toward including cardiovascular-kidney-metabolic health and social factors in risk prediction for CVD,” Khan said in a statement.
Several authors disclosed ties to the biopharmaceutical industry.
2005 to 2023 Saw More U.S. Women Never Screened for Cervical Cancer 
2011 to 2021 Saw Heart Failure-Related Hospitalization Rise in CKD 
Machine Learning Model IDs Heart Failure With Reduced Ejection Fraction Using Routine Lab Indicators 
Addition of CAC to PREVENT-ASCVD Equations May Improve Predictive Utility in Certain Patients .jpg)
Warning Symptoms, Clinical History Can Predict Sudden Cardiac Arrest .jpg)
Micro-, Nanoplastics Detected More Often in Patients With STEMI 
AI Can Accurately Detect Left Ventricular Dysfunction From Electrocardiograms 
Differences in Cardiovascular Risk Factor Prevalence ID"d for South Asian Adults 
