Document Detail


A comparison of glomerular filtration rate estimating equation performance in an older adult population sample.
MedLine Citation:
PMID:  21928611     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
The purpose of this study was to compare the performance of four commonly used glomerular filtration rate (GFR) estimating equations in an older, ethnically diverse sample using a descriptive correlational design. A convenience sample of 495 ethnically diverse adults aged 65 or older were observed via a retrospective record review. Average age was 73 years, and 76% were female. They were 58% African-American and 23% Latino. The estimated GFRs by the various equations were highly correlated MANOVA revealed significant differences between the equations. Chronic kidney disease (CKD) stage distribution was significantly different when examined by the equations. Because pharmacokinetic studies are based on creatinine clearance, the Cockcroft-Gault equation is more appropriate for calculating drug dosages. However, because the CKD Epidemiology Collaboration equation was derived from the most similar and representative sample, and currently offers the greatest discrimination at all levels, it should be used in preference to other equations for the classification and trending of renal function in older minority patients.
Authors:
Kathryn Daniel; Carolyn L Cason; Sachin Shrestha
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Nephrology nursing journal : journal of the American Nephrology Nurses' Association     Volume:  38     ISSN:  1526-744X     ISO Abbreviation:  Nephrol Nurs J     Publication Date:    2011 Jul-Aug
Date Detail:
Created Date:  2011-09-20     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100909377     Medline TA:  Nephrol Nurs J     Country:  United States    
Other Details:
Languages:  eng     Pagination:  351-6     Citation Subset:  N    
Affiliation:
Adult/Gerontologic Nurse Practitioner Program, University of Texas at Arlington, Arlington, TX, USA. kdaniel@uta.edu
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