Predicting survival in patients requiring renal replacement therapy after cardiac surgery

Background. We sought to develop and internally validate a prediction score for all- cause in- hospital mortality in patients who have acute renal failure and require renal replacement therapy after cardiac surgery. Methods. From January 1992 to July 2001, 136 of 14,000 patients ( 0.9%) had acute renal failure requiring renal replacement therapy after cardiac surgery. Multivariate logistic regression analysis, based on pre - renal replacement therapy variables, was used to construct a predictive score for all causes of in- hospital mortality. Subsequently, the score was validated in 27 patients who underwent surgery between August 2001 and March 2003. Results. In- hospital mortality was 58% ( 79 of 136). From the logistic regression model, we assigned a score ( range, 0 to 6) based on the presence of independent predictors of operative mortality ( preoperative creatinine <= 1.5 mg/ dL [ odds ratio ( OR) = 5.0], hypertension [ OR = 4.4], predialysis coma [ OR = 9.6], sepsis [ OR = 6.4], and total bilirubin >= 2 mg/ dL [ OR = 5.6]). Higher scores strongly predicted mortality: patients who scored 3 or higher before the initiation dialysis ( n = 54), had a mortality rate of 94% ( 51 of 54). In contrast, patients who scored 1 or less on this scale ( n = 36), had a mortality of 16% ( 6 of 36). In the validation cohort, the sensitivity of the new score at the cutoff of 2 or fewer points versus 3 or more points was 0.71, the specificity was 0.90, the positive predictive value was 0.92, and the negative predictive value was 0.64. Conclusions. The prediction score represents a simple and accurate tool for predicting in- hospital mortality associated with renal replacement therapy for cardiac surgery patients before the institution of this resource-intensive treatment.