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Incorporating Kidney Disease Measures Into Cardiovascular Risk Prediction: Development And Validation In 9 Million Adults From 72 Datasets, Kunihiro Matsushita, Simerjot K. Jassal, Yingying Sang, Shoshana H. Ballew, Morgan E. Grams, Aditya Surapaneni, Johan Arnlov, Nisha Bansal, Milica Bozic, Tazeen H. Jafar
Incorporating Kidney Disease Measures Into Cardiovascular Risk Prediction: Development And Validation In 9 Million Adults From 72 Datasets, Kunihiro Matsushita, Simerjot K. Jassal, Yingying Sang, Shoshana H. Ballew, Morgan E. Grams, Aditya Surapaneni, Johan Arnlov, Nisha Bansal, Milica Bozic, Tazeen H. Jafar
Section of Nephrology
Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. "CKD Patch" is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures.
Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several "CKD Patches" incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) …