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Journal of nephrology · Jan 2012
Meta AnalysisA population-based approach for the definition of chronic kidney disease: the CKD Prognosis Consortium.
- Massimo Cirillo, Cinzia Lombardi, Alessandra Antonia Mele, Fabiana Marcarelli, and Giancarlo Bilancio.
- Department of Medicine, Salerno Medical School, University of Salerno, Baronissi, Italy. mcirillo@unisa.it
- J. Nephrol. 2012 Jan 1; 25 (1): 7-12.
IntroductionThe Kidney Disease: Improving Global Outcomes (KDIGO) foundation promoted the establishment of the Chronic Kidney Disease (CKD) Prognosis Consortium to meta-analyze the association of estimated glomerular filtration rate (eGFR) and albuminuria with incidence of various outcomes in samples of general populations from all over the world.MethodsVariables in meta-analysis included eGFR by the Modification of Diet in Renal Disease (MDRD) Study equation, the urinary albumin to creatinine ratio (uACR) as index of albuminuria, together with proteinuria at dipstick urinalysis and classical markers of cardiovascular risk. Overall, 105,872 participants had uACR measurements, and 1,128,310 participants had dipstick measurements.ResultsThe association with mortality was continuous over the whole range of uACR/proteinuria and J-shaped for eGFR which was associated with an excess risk for values <75 and ≥120 ml/min per 1.73 m². Results were similar for the association of eGFR or uACR/proteinuria with renal failure. The associations of eGFR and uACR/proteinuria with death or renal failure were independent of each other. Findings were consistent across population samples from North America, Asia, Oceania and Europe, as well as in individuals with age <65 years and individuals with age ≥65 years.ConclusionsData support the threshold of 60 ml/min for CKD definition but suggest that eGFR in the range 60-74 ml/min could represent the early stages of CKD. This first set of results of the CKD Prognosis Consortium represents an important step in the evidence-based definition of CKD. Conclusions should be reevaluated with eGFR calculation by equations less biased for normal-high eGFR.
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