OBJECTIVE: The authors identified risk factors for acute kidney injury (AKI) defined by risk, injury, failure, loss, end-stage (RIFLE) criteria after aortic surgery with cardiopulmonary bypass and constructed a simplified risk score for the prediction of AKI. DESIGN: Retrospective and observational. SETTING: Single large university hospital. PARTICIPANTS: Patients (737) who underwent aortic surgery with cardiopulmonary bypass between 1997 and 2010. MAIN RESULTS: Multivariate logistic regression analysis was used to evaluate risk factors. A scoring model was developed in a randomly selected derivation cohort (n = 417), and was validated on the remaining patients. The scoring model was developed with a score based on regression β-coefficient, and was compared with previous indices as measured by the area under the receiver operating characteristic curve (AUC). The incidence of AKI was 29.0%, and 5.8% required renal replacement therapy. Independent risk factors for AKI were age older than 60 years, preoperative glomerular filtration rate <60 mL/min/1.73 m(2), left ventricular ejection fraction <55%, operation time >7 hours, intraoperative urine output <0.5 mL/kg/h, and intraoperative furosemide use. The authors made a score by weighting them at 1 point each. The risk score was valid in predicting AKI, and the AUC was 0.74 [95% confidence interval (CI): 0.69 to 0.79], which was similar to that in the validation cohort: 0.74 (95% CI: 0.69 to 0.80; p = 0.97). The risk-scoring model showed a better performance compared with previously reported indices. CONCLUSIONS: The model would provide a simplified clinical score stratifying the risk of postoperative AKI in patients undergoing aortic surgery.
OBJECTIVE: The authors identified risk factors for acute kidney injury (AKI) defined by risk, injury, failure, loss, end-stage (RIFLE) criteria after aortic surgery with cardiopulmonary bypass and constructed a simplified risk score for the prediction of AKI. DESIGN: Retrospective and observational. SETTING: Single large university hospital. PARTICIPANTS: Patients (737) who underwent aortic surgery with cardiopulmonary bypass between 1997 and 2010. MAIN RESULTS: Multivariate logistic regression analysis was used to evaluate risk factors. A scoring model was developed in a randomly selected derivation cohort (n = 417), and was validated on the remaining patients. The scoring model was developed with a score based on regression β-coefficient, and was compared with previous indices as measured by the area under the receiver operating characteristic curve (AUC). The incidence of AKI was 29.0%, and 5.8% required renal replacement therapy. Independent risk factors for AKI were age older than 60 years, preoperative glomerular filtration rate <60 mL/min/1.73 m(2), left ventricular ejection fraction <55%, operation time >7 hours, intraoperative urine output <0.5 mL/kg/h, and intraoperative furosemide use. The authors made a score by weighting them at 1 point each. The risk score was valid in predicting AKI, and the AUC was 0.74 [95% confidence interval (CI): 0.69 to 0.79], which was similar to that in the validation cohort: 0.74 (95% CI: 0.69 to 0.80; p = 0.97). The risk-scoring model showed a better performance compared with previously reported indices. CONCLUSIONS: The model would provide a simplified clinical score stratifying the risk of postoperative AKI in patients undergoing aortic surgery.
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