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Medline ® Abstract for Reference 8

of 'Calculation of the creatinine clearance'

8
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Equations to estimate creatinine excretion rate: the CKD epidemiology collaboration.
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Ix JH, Wassel CL, Stevens LA, Beck GJ, Froissart M, Navis G, Rodby R, Torres VE, Zhang YL, Greene T, Levey AS
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Clin J Am Soc Nephrol. 2011 Jan;6(1):184-91. Epub 2010 Oct 21.
 
BACKGROUND AND OBJECTIVES: Creatinine excretion rate (CER) indicates timed urine collection accuracy. Although equations to estimate CER exist, their bias and precision are untested and none simultaneously include age, sex, race, and weight.
DESIGN, SETTING, PARTICIPANTS,& MEASUREMENTS: Participants (n = 2466) from three kidney disease trials were randomly allocated into equation development (2/3) and internal validation (1/3) data sets. CER served as the dependent variable in linear regression to develop new equations. Their stability was assessed within the internal validation data set. Among 987 individuals from three additional studies the equations were externally validated and compared with existing equations.
RESULTS: Mean age was 46 years, 42% were women, and 9% were black. Age, sex, race, weight, and serum phosphorus improved model fit. Two equations were developed, with or without serum phosphorus. In external validation, the new equations showed little bias (mean difference [measured - estimated CER]-0.7% [95% confidence interval -2.5% to 1.0%]and 0.3% [95% confidence interval -2.6% to 3.1%], respectively) and moderate precision (estimated CER within 30% of measured CER among 79% [76% to 81%]and 81% [77% to 85%], respectively). Corresponding numbers within 15% were 51% [48% to 54%]and 54% [50% to 59%]). Compared with existing equations, the new equations had similar accuracy but showed less bias in individuals with high measured CER.
CONCLUSIONS: CER can be estimated with commonly available variables with little bias and moderate precision, which may facilitate assessment of accuracy of timed urine collections.
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Division of Nephrology and Hypertension, Department of Medicine, University of California San Diego, and San Diego VA Healthcare System, 3350 La Jolla Village Drive, Mail Code 111-H, San Diego, CA 92161, USA. joeix@ucsd.edu
PMID