BACKGROUND: A simple method to calculate estimated creatinine clearance using two serum creatinine concentration (Cr) values in acute kidney injury (AKI) was developed (eCrCl-AKI). We aimed to evaluate its accuracy and to clarify its contribution to the classification of AKI. METHODS: We validated the errors in eCrCl-AKI in a simulation study after various reductions in creatinine clearance (CrCl) at various levels of chronic kidney disease (CKD). We compared the eCrCl-AKI-based classification of RIFLE criteria with the Cr-based classification or that proposed by Waikar and Bonventre. The regression equations of eCrCl-AKI on time were determined and Cr values were reconstructed by creatinine kinetics substituting CrCl with eCrCl-AKI in actual patients. RESULTS: Most errors in eCrCl-AKI were relatively small (from -13.6 to +7.9%) with the exception of two Cr values that straddled the changing trend of Cr. The classification according to RIFLE criteria based on Cr was unstable and did not enable adequate classification, especially in milder reductions of CrCl with advanced CKD. The classification based on eCrCl-AKI was stable and enabled adequate classification. There were good agreements between measured Cr and reconstructed Cr with eCrCl-AKI. The regression equations of eCrCl-AKI revealed changes of renal function that were unexpected only from fluctuations of Cr. CONCLUSIONS: eCrCl-AKI can provide relatively accurate estimates for fluctuating CrCl. eCrCl-AKI enables more stable and earlier classification of AKI than Cr, at least in the simulation study. The more widespread use of eCrCl-AKI in actual clinical settings of AKI is necessary to evaluate this formula.
BACKGROUND: A simple method to calculate estimated creatinine clearance using two serum creatinine concentration (Cr) values in acute kidney injury (AKI) was developed (eCrCl-AKI). We aimed to evaluate its accuracy and to clarify its contribution to the classification of AKI. METHODS: We validated the errors in eCrCl-AKI in a simulation study after various reductions in creatinine clearance (CrCl) at various levels of chronic kidney disease (CKD). We compared the eCrCl-AKI-based classification of RIFLE criteria with the Cr-based classification or that proposed by Waikar and Bonventre. The regression equations of eCrCl-AKI on time were determined and Cr values were reconstructed by creatinine kinetics substituting CrCl with eCrCl-AKI in actual patients. RESULTS: Most errors in eCrCl-AKI were relatively small (from -13.6 to +7.9%) with the exception of two Cr values that straddled the changing trend of Cr. The classification according to RIFLE criteria based on Cr was unstable and did not enable adequate classification, especially in milder reductions of CrCl with advanced CKD. The classification based on eCrCl-AKI was stable and enabled adequate classification. There were good agreements between measured Cr and reconstructed Cr with eCrCl-AKI. The regression equations of eCrCl-AKI revealed changes of renal function that were unexpected only from fluctuations of Cr. CONCLUSIONS: eCrCl-AKI can provide relatively accurate estimates for fluctuating CrCl. eCrCl-AKI enables more stable and earlier classification of AKI than Cr, at least in the simulation study. The more widespread use of eCrCl-AKI in actual clinical settings of AKI is necessary to evaluate this formula.
Authors: Andrew S Levey; Kai-Uwe Eckardt; Yusuke Tsukamoto; Adeera Levin; Josef Coresh; Jerome Rossert; Dick De Zeeuw; Thomas H Hostetter; Norbert Lameire; Garabed Eknoyan Journal: Kidney Int Date: 2005-06 Impact factor: 10.612
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