• Emerson Quintino Lima, Maria T Zanetta Dirce, Isac Castro, and Luis Yu.
• Division of Nephrology, School of Medicine, University of Sao Paulo, São Paulo, Brazil. equintino@famerp.br
• Ren Fail. 2005 Jan 1;27(5):547-56.

BackgroundRisk stratification and prediction of outcome in acute renal failure patients in the intensive care unit are important determinants for improvement of patient care and design of clinical trials.MethodsIn order to identify mortality risks factors and validate general and specific predictive models for acute renal failure (ARF) patients in the intensive care unit (ICU), 324 patients were prospectively evaluated. Multivariate analysis by logistic regression was utilized for identification of mortality risk factors. Discrimination and calibration were used to evaluate the performance of the following models at referral to nephrologist and at initiation of renal replacement therapy: APACHE II, SAPS II, LODS, and ATN-ISI. Organ failure was assessed by SOFA and OSF.ResultsThe hospital mortality rate was 85%. The identified mortality risk factors were: age > or = 65 yr, BUN > or = 70 mg/dL, ARF of septic origin, and previous hypertension. Serum creatinine > or = 3.5 mg/dL, systolic blood pressure > or = 100 mm Hg, and normal consciousness were associated with mortality risk reduction. Performance of all prognostic models was disappointing with unsatisfactory calibration and underestimation of mortality on the day of referral to the nephrologist and at initiation of renal replacement therapy.ConclusionsCross-validation of prognostic models for ARF resulted in poor performance of all studied scores. Therefore, a specific model is still warranted for the design of clinical trials, comparison of studies, and for prediction of outcome in ARF patients, especially in the ICU.

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