Format

Send to

Choose Destination
See comment in PubMed Commons below
Curr Opin Nephrol Hypertens. 2012 Nov;21(6):612-8. doi: 10.1097/MNH.0b013e328359072f.

Risk prediction in chronic kidney disease: pitfalls and caveats.

Author information

  • 1Seven Oaks General Hospital, University of Manitoba, Winnipeg, Manitoba, Canada.

Abstract

PURPOSE OF REVIEW:

This review aims to describe the challenges and highlight recent advances in the field of risk prediction for patients with chronic kidney disease (CKD). We first focus on methods of model development and metrics of model performance in general, and then highlight important risk prediction tools for patients with CKD, for prediction of kidney failure and all-cause mortality.

RECENT FINDINGS:

Investigators have used data from patients with CKD stages 1-5 and developed models for predicting the progression to kidney failure and all-cause mortality. Models for kidney failure have included estimated glomerular filtration rate, albuminuria, demographic and laboratory variables, and have achieved excellent discrimination. In contrast, model performance for prediction of all-cause mortality has been relatively modest. No validated models exist for predicting the risk of cardiovascular events in patients with CKD.

SUMMARY:

Models for predicting kidney failure in patients with CKD are highly accurate and clinically usable. The kidney failure risk equation includes routinely collected laboratory data and can predict the progression of CKD to kidney failure with accuracy. Additional validation of the risk equation and development of new models for all-cause mortality and cardiovascular events in patients with CKD are needed.

[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Lippincott Williams & Wilkins
    Loading ...
    Write to the Help Desk