Predicting Risk of Cardiovascular Disease EVENTs Equation for Adverse Cardio-Kidney Outcomes in CKD Population

The Predicting Risk of Cardiovascular Disease EVENTs score outperformed previous models in prediction of cardio-kidney outcomes. Adding albuminuria to the Predicting Risk of Cardiovascular Disease EVENTs score showed further improvement in patients with CKD. Among East Asian participants, Predicting Risk of Cardiovascular Disease EVENTs provided modest gains in cardiovascular prediction but prominent improvements in predicting kidney outcomes.

CKD substantially increases cardiovascular disease (CVD) and mortality risks, yet few models account for integrated cardio-kidney outcomes (CKOs). The American Heart Association's Predicting Risk of CVD EVENTs (PREVENT) score incorporates kidney-specific measures; however, its accuracy for CKOs in patients with CKD remains unclear. We aimed to evaluate PREVENT for CKOs against the pooled cohort equation (PCE) and systematic coronary risk evaluation 2 (SCORE2) in two ethnically distinct CKD cohorts: KoreaN Cohort Study for Outcome in Patients With CKD (KNOW-CKD) from South Korea and Chronic Renal Insufficiency Cohort from the United States.

This study included 4,268 patients with CKD and no known CVD (chronic renal insufficiency cohort: 2,530, KNOW-CKD: 1,738). We compared PREVENT (CVD and atherosclerotic CVD versions) with the PCE and SCORE2. The primary outcome was CKO, a composite of major adverse kidney events (≥50% eGFR decline or kidney failure requiring replacement therapy) and four-point major adverse cardiovascular events (4P-MACEs). Secondary outcomes included individual components and all-cause mortality.

The PREVENT-CVD score showed superior predictive accuracy for CKO (Harrell C, 0.688; 95% confidence interval [CI], 0.675 to 0.701) compared with PREVENT-atherosclerotic CVD (delta C [ΔC]=-0.009; 95% CI, -0.011 to -0.007), PCE (ΔC=-0.104; 95% CI, -0.113 to -0.095), and SCORE2 (ΔC=-0.106; 95% CI, -0.114 to -0.097). This superiority was driven by robust prediction for major adverse kidney event, along with significant improvements in reclassification and discrimination for 4P-MACE and all-cause mortality. Although predictive gains for 4P-MACE were attenuated in the KNOW-CKD cohort, adding albuminuria further enhanced predictive performance for primary outcome.

The PREVENT-CVD equation outperformed traditional cardiovascular risk models in predicting integrated CKOs in patients with CKD. Its consistent discrimination across both cardiovascular and kidney events suggests that PREVENT may reflect the shared pathophysiology of cardio-kidney disease and support broader risk stratification in CKD.

This article contains a podcast at https://dts.podtrac.com/redirect.mp3//www.asn-online.org/media/podcast/JASN/2026_07_29_KTS_July2026.mp3.