Comparison of Cardiovascular Disease Risk Estimates Using Enhanced PREVENT Equations
Year: 2026
Type: article
Abstract: INTRODUCTION: The 2023 Predicting Risk of Cardiovascular Disease EVENTs equations for 10-year cardiovascular disease were developed by the American Heart Association to improve upon the 2013 Pooled Cohort Equations. This study sought to compare risk reclassification using the Predicting Risk of Cardiovascular Disease EVENTs equations with and without the use of the optional predictors HbA1c and urine albumin-creatinine ratio. METHODS: This was a cross-sectional study of adults aged 30-79 years participating in the National Health and Nutrition Examination Survey from 2015 to 2020. Ten-year cardiovascular disease estimates stratified by diabetes status using the base Predicting Risk of Cardiovascular Disease EVENTs equations and the enhanced Predicting Risk of Cardiovascular Disease EVENTs equations, including HbA1c and urine albumin-creatinine ratio, were examined. RESULTS: The study included 8,293 participants (weighted mean age of 51 years, 52% female, 13% with diabetes) representing 147.9 million U.S. adults. Estimated 10-year cardiovascular disease risks using the base and enhanced Predicting Risk of Cardiovascular Disease EVENTs equations were within 5 percentage points for 99% of adults without diabetes and 82% of adults with diabetes. Individuals with HbA1c ≥9.0% had a higher mean risk from the enhanced equations of 17.8% (95% CI=15.9%, 19.7%) than the mean risk from the base equations of 11.8% (95% CI=10.7%, 12.9%). This finding was mirrored with urine albumin-creatinine ratio. Individuals with urine albumin-creatinine ratio ≥300 mg/g had a higher mean risk from the enhanced equations at 36.1% (95% CI=33.2%, 39.1%) than the mean risk from the base equations of 23.4% (95% CI=20.0%, 26.9%). CONCLUSIONS: Inclusion of HbA1c and urine albumin-creatinine ratio in the Predicting Risk of Cardiovascular Disease EVENTs equations provides an opportunity for greater individualization of cardiovascular disease risk estimation in adults with diabetes but little benefit in populations without diabetes.
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,300
OpenAlex ID: W7164643818