Tomoko Fujii1, Shigehiko Uchino, Masanori Takinami, Rinaldo Bellomo. 1. Intensive Care Unit, Department of Anesthesiology, The Jikei University School of Medicine, Tokyo, Japan, †Department of Intensive Care, Austin Hospital, Melbourne, Victoria, Australia.
Abstract
BACKGROUND AND OBJECTIVES: AKI is a major clinical problem and predictor of outcome in hospitalized patients. In 2013, the Kidney Disease: Improving Global Outcomes (KDIGO) group published the third consensus AKI definition and classification system after the Risk, Injury, Failure, Loss of Kidney Function, and End-Stage Kidney Disease (RIFLE) and the Acute Kidney Injury Network (AKIN) working group systems. It is unclear which system achieves optimal prognostication in hospital patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A retrospective observational study using hospital laboratory, admission, and discharge databases was performed that included adult patients admitted to a teaching hospital in Tokyo, Japan between April 1, 2008, and October 31, 2011. AKI occurring during each hospital stay was identified, and discriminative ability of each AKI classification system based on serum creatinine for the prediction of hospital mortality was assessed. The receiver operating characteristic curve, a graphical measure of test performance, and the area under the curve were used to evaluate how classifications preformed on the study population. RESULTS: In total, 49,518 admissions were studied, of which 11.0% were diagnosed with RIFLE criteria and 11.6% were diagnosed with KDIGO criteria, but only 4.8% were diagnosed with AKIN criteria. Overall hospital mortality was 3.0%. AKI staging and hospital mortality were closely correlated in all systems. Discrimination for hospital mortality was similar for RIFLE and KDIGO criteria (area under the curve=0.77 versus 0.78; P=0.02), whereas AKIN discrimination was inferior (area under the curve=0.69 versus RIFLE [P<0.001] versus KDIGO [P<0.001]). CONCLUSION: Among hospital patients, KDIGO and RIFLE criteria achieved similar discrimination, but the discrimination of AKIN was inferior.
BACKGROUND AND OBJECTIVES: AKI is a major clinical problem and predictor of outcome in hospitalized patients. In 2013, the Kidney Disease: Improving Global Outcomes (KDIGO) group published the third consensus AKI definition and classification system after the Risk, Injury, Failure, Loss of Kidney Function, and End-Stage Kidney Disease (RIFLE) and the Acute Kidney Injury Network (AKIN) working group systems. It is unclear which system achieves optimal prognostication in hospital patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A retrospective observational study using hospital laboratory, admission, and discharge databases was performed that included adult patients admitted to a teaching hospital in Tokyo, Japan between April 1, 2008, and October 31, 2011. AKI occurring during each hospital stay was identified, and discriminative ability of each AKI classification system based on serum creatinine for the prediction of hospital mortality was assessed. The receiver operating characteristic curve, a graphical measure of test performance, and the area under the curve were used to evaluate how classifications preformed on the study population. RESULTS: In total, 49,518 admissions were studied, of which 11.0% were diagnosed with RIFLE criteria and 11.6% were diagnosed with KDIGO criteria, but only 4.8% were diagnosed with AKIN criteria. Overall hospital mortality was 3.0%. AKI staging and hospital mortality were closely correlated in all systems. Discrimination for hospital mortality was similar for RIFLE and KDIGO criteria (area under the curve=0.77 versus 0.78; P=0.02), whereas AKIN discrimination was inferior (area under the curve=0.69 versus RIFLE [P<0.001] versus KDIGO [P<0.001]). CONCLUSION: Among hospital patients, KDIGO and RIFLE criteria achieved similar discrimination, but the discrimination of AKIN was inferior.
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