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CHRONIC KIDNEY DISEASE

CKD-specific ASCVD risk prediction tools

Nature Reviews Nephrology volume 18, page 199 (2022)Cite this article

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Atherosclerotic cardiovascular disease (ASCVD) risk prediction tools developed for the general population might not be valid for patients with chronic kidney disease (CKD). To address this gap, Bundy et al. used a cohort of patients with CKD to develop ten-year ASCVD risk prediction models. Model 1 used pooled cohort equations with CKD cohort-specific coefficients, model 2 included common clinical variables such as urinary albumin-to-creatinine ratio and HbA1c, and model 3 combined kidney and cardiac biomarkers. All models improved ASCVD risk prediction compared with current tools, especially the models that included HbA1c and cardiac biomarkers.

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Original article

  • Bundy, J. D. et al. Risk prediction models for atherosclerotic cardiovascular disease in patients with chronic kidney disease: the CRIC study. J. Am. Soc. Nephrol. 33, 601–611 (2022)

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  1. Nature Reviews Nephrology http://www.nature.com/nrneph

    Monica Wang

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  1. Monica Wang
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Correspondence to Monica Wang.

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Wang, M. CKD-specific ASCVD risk prediction tools. Nat Rev Nephrol 18, 199 (2022). https://doi.org/10.1038/s41581-022-00557-0

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  • DOI: https://doi.org/10.1038/s41581-022-00557-0

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