Document Detail

Risk prediction in chronic kidney disease: pitfalls and caveats.
MedLine Citation:
PMID:  23042027     Owner:  NLM     Status:  MEDLINE    
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.
Claudio Rigatto; Manish M Sood; Navdeep Tangri
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Publication Detail:
Type:  Journal Article; Review    
Journal Detail:
Title:  Current opinion in nephrology and hypertension     Volume:  21     ISSN:  1473-6543     ISO Abbreviation:  Curr. Opin. Nephrol. Hypertens.     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-10-18     Completed Date:  2013-03-29     Revised Date:  2013-05-02    
Medline Journal Info:
Nlm Unique ID:  9303753     Medline TA:  Curr Opin Nephrol Hypertens     Country:  England    
Other Details:
Languages:  eng     Pagination:  612-8     Citation Subset:  IM    
Seven Oaks General Hospital, University of Manitoba, Winnipeg, Manitoba, Canada.
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MeSH Terms
Cardiovascular Diseases / diagnosis,  etiology*,  mortality
Decision Support Techniques*
Disease Progression
Middle Aged
Models, Biological*
Renal Insufficiency / diagnosis,  etiology*,  mortality
Renal Insufficiency, Chronic / complications*,  diagnosis,  mortality
Risk Assessment
Risk Factors
Time Factors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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