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Predicting Hospital Outcomes of Acute Kidney Injury Defined by 48-Hour KDIGO Classification in Critically Ill Patients: The Role of Urine Output Criteria
摘要
BACKGROUND: Acute kidney injury (AKI) as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) classification system, is associated with poor outcomes in critically ill patients. However, the clinical role of urine output criteria in the KDIGO classification system has rarely been comprehensively validated. The current study was designed to compare the use of creatinine criteria, urine output criteria, and a combination of the two, as part of the KDIGO classification system, within 48 hours of intensive care unit (ICU) admission. The impact of these criteria on the sensitivity of detecting patients at high-risk or with established AKI, and their ability to predict hospital outcomes were also assessed. METHODS: The clinical data of patients admitted to the ICUs at a tertiary medical center in southern Taiwan in 2012 was collected from the clinical information system. The exclusion criteria were age ＜ 18 years, ICU stays for ＜ 48 hours, insufficient data for analysis, and end-stage renal disease under renal replacement therapy. Urine output was manually reviewed during the first 48 hours of ICU admission. Patients were classified as non-AKI, stage 1 AKI, stage 2 AKI, and stage 3 AKI according to their urine output criteria, the creatinine criteria, and a combination of both criteria using the KDIGO classification system. A comparison of performance of the above criteria was conducted. RESULTS: A total of 1,835 patients were included for analysis. Their median age was 65.0 years with an interquartile range (IQR), 53.9-78.1. The percentage of males was 64.9%. The overall case fatality rate was 23.4%. The incidence of AKI as defined by the creatinine criteria, urine output criteria, and both criteria was 40.2%, 44.5%, and 60.4%, respectively. Following the addition of urine output criteria to the classification system, 370 of the 1,097 patients were reclassified into the AKI group. In all criteria, the mortality rate increased as AKI severity increased. The odds ratio for mortality significantly increased in the univariable analysis for all AKI stages across all criteria. However, in the multivariable analysis, the odds ratio for stage 1 AKI by creatinine and urine output criteria did not significantly increase (odds ratio, 1.21; IQR, 0.87-1.68; P = 0.265). CONCLUSION: The use of urine output criteria increased the sensitivity of AKI identification compared to using only creatinine criteria for AKI grading. The combination of urine output and creatinine criteria would blunt the prediction of mortality risk in stage 1 AKI using the KDIGO classification system.
延伸閱讀
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