Abstract
IntroductionRecently, the Kidney Disease: Improving Global Outcomes (KDIGO) proposed a new definition and classification of acute kidney injury (AKI) on the basis of the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage renal failure) and AKIN (Acute Kidney Injury Network) criteria, but comparisons of the three criteria in critically ill patients are rare.MethodsWe prospectively analyzed a clinical database of 3,107 adult patients who were consecutively admitted to one of 30 intensive care units of 28 tertiary hospitals in Beijing from 1 March to 31 August 2012. AKI was defined by the RIFLE, AKIN, and KDIGO criteria. Receiver operating curves were used to compare the predictive ability for mortality, and logistic regression analysis was used for the calculation of odds ratios and 95% confidence intervals.ResultsThe rates of incidence of AKI using the RIFLE, AKIN, and KDIGO criteria were 46.9%, 38.4%, and 51%, respectively. KDIGO identified more patients than did RIFLE (51% versus 46.9%, P = 0.001) and AKIN (51% versus 38.4%, P <0.001). Compared with patients without AKI, in-hospital mortality was significantly higher for those diagnosed as AKI by using the RIFLE (27.8% versus 7%, P <0.001), AKIN (32.2% versus 7.1%, P <0.001), and KDIGO (27.4% versus 5.6%, P <0.001) criteria, respectively. There was no difference in AKI-related mortality between RIFLE and KDIGO (27.8% versus 27.4%, P = 0.815), but there was significant difference between AKIN and KDIGO (32.2% versus 27.4%, P = 0.006). The areas under the receiver operator characteristic curve for in-hospital mortality were 0.738 (P <0.001) for RIFLE, 0.746 (P <0.001) for AKIN, and 0.757 (P <0.001) for KDIGO. KDIGO was more predictive than RIFLE for in-hospital mortality (P <0.001), but there was no difference between KDIGO and AKIN (P = 0.12).ConclusionsA higher incidence of AKI was diagnosed according to KDIGO criteria. Patients diagnosed as AKI had a significantly higher in-hospital mortality than non-AKI patients, no matter which criteria were used. Compared with the RIFLE criteria, KDIGO was more predictive for in-hospital mortality, but there was no significant difference between AKIN and KDIGO.
Highlights
The Kidney Disease: Improving Global Outcomes (KDIGO) proposed a new definition and classification of acute kidney injury (AKI) on the basis of the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage renal failure) and AKIN (Acute Kidney Injury Network) criteria, but comparisons of the three criteria in critically ill patients are rare
Study cohort This study used a database from a prospective, multicenter, observational study which investigated the epidemiology of AKI in critically ill patients at 30 intensive care unit (ICU) of 28 tertiary hospitals in Beijing, China, from 1 March to 31 August 2012. (For a complete list of those hospitals and the persons responsible for the acquisition of data, see Additional file 2.) All patients who were older than 18 years and who were consecutively admitted to any participating ICU during the observational period were enrolled
Predictive ability for mortality Irrespectively of which definition was used, AKI was independently associated with in-hospital mortality even after adjustment for age, gender, diabetes, hypertension, chronic kidney disease, chronic heart failure, and Sequential Organ Failure Assessment (SOFA) score (Table 5)
Summary
The Kidney Disease: Improving Global Outcomes (KDIGO) proposed a new definition and classification of acute kidney injury (AKI) on the basis of the RIFLE (Risk, Injury, Failure, Loss of kidney function, and End-stage renal failure) and AKIN (Acute Kidney Injury Network) criteria, but comparisons of the three criteria in critically ill patients are rare. The classification includes three grades of severity of AKI (risk, injury, and failure) according to relative changes in serum creatinine (SCr) and urine output and two outcomes (loss of kidney function and end-stage kidney disease, or ESKD). It has been evaluated in many studies of critically ill patients with AKI and has shown good relevance for diagnosing and classifying the severity of AKI as well as comparable predictive ability for mortality [7,9,10,11,12,13]
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