BACKGROUND: The Kidney Disease: Improving Global Outcomes (KDIGO) group proposed to adopt the 48-h time window for the 0.3 mg/dL rise in serum creatinine (sCr) proposed by the Acute Kidney Injury Network (AKIN) group as a modification to the original risk, injury, failure, loss, and end-stage renal disease criteria, keeping the 7-day window for the 50 % increase in sCr from baseline. The present study evaluates the prevalence of acute kidney injury (AKI) and the accuracy of predicting mortality based on the KDIGO and AKIN criteria. PATIENTS AND METHODS: We retrospectively studied a cohort of 2579 patients admitted to the intensive care unit of Nagoya University Hospital between 2005 and 2009. RESULTS: The total AKI prevalence was higher according to the KDIGO than to the AKIN criteria (38.4 versus 29.5 %). In-hospital mortality rates were higher among 238 patients classified as non-AKI by the AKIN but AKI by the KDIGO criteria than among those classified as non-AKI by both criteria (7.1 versus 2.7 %). Survival curves generated using KDIGO significantly differed among all stages, but not between AKIN stages I and II. Multivariate analysis showed that KDIGO criteria were better in a statistical model than the AKIN criteria according to the Akaike information criterion. Harrell's C statistic was greater for the KDIGO than for the AKIN criteria. CONCLUSIONS: The KDIGO criteria have improved sensitivity without compromising specificity for AKI and might predict mortality at least as well as the AKIN criteria.
BACKGROUND: The Kidney Disease: Improving Global Outcomes (KDIGO) group proposed to adopt the 48-h time window for the 0.3 mg/dL rise in serum creatinine (sCr) proposed by the Acute Kidney Injury Network (AKIN) group as a modification to the original risk, injury, failure, loss, and end-stage renal disease criteria, keeping the 7-day window for the 50 % increase in sCr from baseline. The present study evaluates the prevalence of acute kidney injury (AKI) and the accuracy of predicting mortality based on the KDIGO and AKIN criteria. PATIENTS AND METHODS: We retrospectively studied a cohort of 2579 patients admitted to the intensive care unit of Nagoya University Hospital between 2005 and 2009. RESULTS: The total AKI prevalence was higher according to the KDIGO than to the AKIN criteria (38.4 versus 29.5 %). In-hospital mortality rates were higher among 238 patients classified as non-AKI by the AKIN but AKI by the KDIGO criteria than among those classified as non-AKI by both criteria (7.1 versus 2.7 %). Survival curves generated using KDIGO significantly differed among all stages, but not between AKIN stages I and II. Multivariate analysis showed that KDIGO criteria were better in a statistical model than the AKIN criteria according to the Akaike information criterion. Harrell's C statistic was greater for the KDIGO than for the AKIN criteria. CONCLUSIONS: The KDIGO criteria have improved sensitivity without compromising specificity for AKI and might predict mortality at least as well as the AKIN criteria.
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