Predicting acute renal failure after cardiac surgery: external validation of two new clinical scores

Different scores to predict acute kidney injury after cardiac surgery have been developed recently. The purpose of this study was to validate externally two clinical scores developed at Cleveland and Toronto.

A retrospective analysis was conducted of a prospectively maintained database of all cardiac surgeries performed during a 5-yr period (2002 to 2006) at a University Hospital in Madrid, Spain. Acute kidney injury was defined as the need for renal replacement therapy. For evaluation of the performance of both models, discrimination and calibration were measured.

Frequency of acute kidney injury after cardiac surgery was 3.7% in the cohort used to validate the Cleveland score and 3.8% in the cohort used to validate the Toronto score. Discrimination of both models was excellent, with values for the areas under the receiving operator characteristics curves of 0.86 (95% confidence interval 0.81 to 0.9) and 0.82 (95% confidence interval 0.76 to 0.87), respectively. Calibration was poor, with underestimation of the risk for acute kidney injury except for patients within the very-low-risk category. The performance of both models clearly improved after recalibration.

Both models were found to be very useful to discriminate between patients who will and will not develop acute kidney injury after cardiac surgery; however, before using the scores to estimate risk probabilities at a specific center, recalibration may be needed.