Literature DB >> 20138414

Comparison of the prevalence and mortality risk of CKD in Australia using the CKD Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Study GFR estimating equations: the AusDiab (Australian Diabetes, Obesity and Lifestyle) Study.

Sarah L White1, Kevan R Polkinghorne, Robert C Atkins, Steven J Chadban.   

Abstract

BACKGROUND: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) is more accurate than the Modification of Diet in Renal Disease (MDRD) Study equation. We applied both equations in a cohort representative of the Australian adult population. STUDY
DESIGN: Population-based cohort study. SETTING & PARTICIPANTS: 11,247 randomly selected noninstitutionalized Australians aged >or= 25 years who attended a physical examination during the baseline AusDiab (Australian Diabetes, Obesity and Lifestyle) Study survey. PREDICTORS & OUTCOMES: Glomerular filtration rate (GFR) was estimated using the MDRD Study and CKD-EPI equations. Kidney damage was defined as urine albumin-creatinine ratio >or= 2.5 mg/mmol in men and >or= 3.5 mg/mmol in women or urine protein-creatinine ratio >or= 0.20 mg/mg. Chronic kidney disease (CKD) was defined as estimated GFR (eGFR) >or= 60 mL/min/1.73 m(2) or kidney damage. Participants were classified into 3 mutually exclusive subgroups: CKD according to both equations; CKD according to the MDRD Study equation, but no CKD according to the CKD-EPI equation; and no CKD according to both equations. All-cause mortality was examined in subgroups with and without CKD. MEASUREMENTS: Serum creatinine and urinary albumin, protein, and creatinine measured on a random spot morning urine sample.
RESULTS: 266 participants identified as having CKD according to the MDRD Study equation were reclassified to no CKD according to the CKD-EPI equation (estimated prevalence, 1.9%; 95% CI, 1.4-2.6). All had an eGFR >or= 45 mL/min/1.73 m(2) using the MDRD Study equation. Reclassified individuals were predominantly women with a favorable cardiovascular risk profile. The proportion of reclassified individuals with a Framingham-predicted 10-year cardiovascular risk >or= 30% was 7.2% compared with 7.9% of the group with no CKD according to both equations and 45.3% of individuals retained in stage 3a using both equations. There was no evidence of increased all-cause mortality in the reclassified group (age- and sex-adjusted hazard ratio vs no CKD, 1.01; 95% CI, 0.62-1.97). Using the MDRD Study equation, the prevalence of CKD in the Australian population aged >or= 25 years was 13.4% (95% CI, 11.1-16.1). Using the CKD-EPI equation, the prevalence was 11.5% (95% CI, 9.42-14.1). LIMITATIONS: Single measurements of serum creatinine and urinary markers.
CONCLUSIONS: The lower estimated prevalence of CKD using the CKD-EPI equation is caused by reclassification of low-risk individuals. Copyright 2010 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20138414     DOI: 10.1053/j.ajkd.2009.12.011

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  91 in total

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Authors:  Andrew S Levey; Lesley A Stevens
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5.  Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts.

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Review 8.  [Diabetic kidney disease - Update 2016].

Authors:  Harald Sourij; Roland Edlinger; Friedrich Prischl; Martin Auinger; Alexandra Kautzky-Willer; Marcus D Säemann; Rudolf Prager; Martin Clodi; Guntram Schernthaner; Gert Mayer; Rainer Oberbauer; Alexander R Rosenkranz
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9.  Estimated GFR and incident cardiovascular disease events in American Indians: the Strong Heart Study.

Authors:  Nawar M Shara; Hong Wang; Mihriye Mete; Yaman Rai Al-Balha; Nameer Azalddin; Elisa T Lee; Nora Franceschini; Stacey E Jolly; Barbara V Howard; Jason G Umans
Journal:  Am J Kidney Dis       Date:  2012-07-25       Impact factor: 8.860

Review 10.  The global burden of chronic kidney disease: estimates, variability and pitfalls.

Authors:  Richard J Glassock; David G Warnock; Pierre Delanaye
Journal:  Nat Rev Nephrol       Date:  2016-12-12       Impact factor: 28.314

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