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SAPS 3 scores at the start of renal replacement therapy predict mortality in critically ill patients with acute kidney injury
Author(s) -
Elizabeth Maccariello,
Carla Valente,
Liogueira,
Hélio Bonomo,
Márcia Ismael,
Jose Eduardo Machado,
Fernanda Baldotto,
Marise Godinho,
Ricardo V. R. Valença,
Eduardo Rocha,
Márcio Soares
Publication year - 2009
Publication title -
kidney international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.499
H-Index - 276
eISSN - 1523-1755
pISSN - 0085-2538
DOI - 10.1038/ki.2009.385
Subject(s) - renal replacement therapy , medicine , acute kidney injury , saps ii , intensive care unit , receiver operating characteristic , multivariate analysis , population , intensive care medicine , kidney disease , emergency medicine , severity of illness , apache ii , nephrology , intensive care , environmental health
Patients can experience acute kidney injury and require renal replacement therapy at any time during their admission to intensive care units. Prognostic scores have been used to characterize and stratify patients by the severity of acute disease, but scores based on findings during the day of admission may not be reliable surrogate markers of the severity of acute illness in this population. The aim of this study was to evaluate the performance of SAPS 3 and MPM(0)-III scores, determined at the start of renal replacement therapy, in 244 patients admitted to 11 units of three hospitals in Rio de Janeiro, Brazil. Continuous renal replacement therapy was used as first indication in 84% of these patients. Discrimination by area under the receiver operating characteristic curve was significantly better for SAPS 3 than for MPM(0)-III, as was the calibration measured by the Hosmer-Lemeshow goodness-of-fit test. Mortality prediction and calibration approached those eventually found when a customized equation of SAPS 3 for Central and South America was used. After adjusting for other relevant covariates in multivariate analyses, both higher prognostic scores and length of stay in the unit prior to the start of renal replacement therapy were the main predictive factors for hospital mortality. Our study shows that a customized SAPS 3 model was accurate in predicting mortality and seems a promising algorithm to characterize and stratify patients in clinical studies.

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