Cardiovascular Risk Prediction in CKD

Shoshana Ballew, Kunihiro Matsushita

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Cardiovascular disease is an important complication for patients with chronic kidney disease (CKD), warranting accurate risk prediction, but clinical guidelines are inconsistent regarding whether or how to use information on measures of CKD for predicting risk. Recent large meta-analyses have shown that key CKD measures (estimated glomerular filtration rate and albuminuria) improve cardiovascular risk prediction beyond traditional risk factors, especially when albuminuria is added to prediction models. In addition, several recent studies have shown that the use of filtration markers other than serum creatinine, cystatin C, and β2-microglobulin can improve cardiovascular risk prediction. In case the goal is to best estimate cardiovascular risk, recent studies have shown that measures reflecting pathophysiological processes in the cardiovascular system, such as coronary artery calcium score or high-sensitivity cardiac troponin T, can be useful in CKD populations. This review compares the current major clinical guidelines and synthesizes the growing body of evidence on traditional and nontraditional predictors for improving cardiovascular risk prediction in persons with CKD.

Original languageEnglish (US)
JournalSeminars in Nephrology
StateAccepted/In press - Jan 1 2018


  • Albuminuria
  • cardiovascular disease
  • estimated glomerular filtration rate
  • risk prediction

ASJC Scopus subject areas

  • Nephrology


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