Equations to estimate creatinine excretion rate: The CKD epidemiology collaboration

Joachim H. Ix, Christina L. Wassel, Lesley A. Stevens, Gerald J. Beck, Marc Froissart, Gerjan Navis, Roger Rodby, Vicente Torres, Yaping Zhang, Tom Greene, Andrew S. Levey

Research output: Contribution to journalArticle

90 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)184-191
Number of pages8
JournalClinical Journal of the American Society of Nephrology
Volume6
Issue number1
DOIs
StatePublished - Jan 1 2011

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Creatinine
Epidemiology
Urine Specimen Collection
Phosphorus
Confidence Intervals
Weights and Measures
Kidney Diseases
Serum
Linear Models

ASJC Scopus subject areas

  • Nephrology
  • Transplantation
  • Epidemiology
  • Critical Care and Intensive Care Medicine

Cite this

Ix, J. H., Wassel, C. L., Stevens, L. A., Beck, G. J., Froissart, M., Navis, G., ... Levey, A. S. (2011). Equations to estimate creatinine excretion rate: The CKD epidemiology collaboration. Clinical Journal of the American Society of Nephrology, 6(1), 184-191. https://doi.org/10.2215/CJN.05030610

Equations to estimate creatinine excretion rate : The CKD epidemiology collaboration. / Ix, Joachim H.; Wassel, Christina L.; Stevens, Lesley A.; Beck, Gerald J.; Froissart, Marc; Navis, Gerjan; Rodby, Roger; Torres, Vicente; Zhang, Yaping; Greene, Tom; Levey, Andrew S.

In: Clinical Journal of the American Society of Nephrology, Vol. 6, No. 1, 01.01.2011, p. 184-191.

Research output: Contribution to journalArticle

Ix, JH, Wassel, CL, Stevens, LA, Beck, GJ, Froissart, M, Navis, G, Rodby, R, Torres, V, Zhang, Y, Greene, T & Levey, AS 2011, 'Equations to estimate creatinine excretion rate: The CKD epidemiology collaboration', Clinical Journal of the American Society of Nephrology, vol. 6, no. 1, pp. 184-191. https://doi.org/10.2215/CJN.05030610
Ix, Joachim H. ; Wassel, Christina L. ; Stevens, Lesley A. ; Beck, Gerald J. ; Froissart, Marc ; Navis, Gerjan ; Rodby, Roger ; Torres, Vicente ; Zhang, Yaping ; Greene, Tom ; Levey, Andrew S. / Equations to estimate creatinine excretion rate : The CKD epidemiology collaboration. In: Clinical Journal of the American Society of Nephrology. 2011 ; Vol. 6, No. 1. pp. 184-191.
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abstract = "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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AU - Froissart, Marc

AU - Navis, Gerjan

AU - Rodby, Roger

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AU - Greene, Tom

AU - Levey, Andrew S.

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N2 - 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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