Adding measures of kidney function on top of the atherosclerotic cardiovascular disease (ASCVD) risk score calculated with traditional factors improves prediction of future CVD risk, according to a study published in the Journal of the American Society of Nephrology. Investigators studied 115,366 participants in the China Cardiometabolic Disease and Cancer Cohort study to assess CVD risks based on albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR; individually, together, and in combination using the Kidney Disease: Improving Global Outcomes [KDIGO] risk categories). Participants were aged 40 and older and were examined prospectively for major CVD events. The study team identified 2,866 major CVD events during 415,111 person-years of follow-up. Across the KDIGO risk categories in ASCVD risk strata, incidence rates and multivariable-adjusted hazard ratios of CVD events increased significantly. After adding eGFR and log (ACR) to a model including the ASCVD risk score, increases in the C statistic for CVD risk prediction were 0.0116 and 0.0254 in the overall study population and in participants with diabetes, respectively. Significantly improved reclassification of CVD risks was seen with the addition of eGFR and log (ACR) to a model with the ASCVD score (net reclassification improvements, 4.78%).