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Interact Cardiovasc Thorac Surg · Oct 2017
Risk model for deaths and renal replacement therapy dependence in patients with acute kidney injury after cardiac surgery.
- Shiren Sun, Feng Ma, Qiaoneng Li, Ming Bai, Yangping Li, Yan Yu, Chen Huang, Hanmin Wang, and Xiaoxuan Ning.
- Department of Nephrology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
- Interact Cardiovasc Thorac Surg. 2017 Oct 1; 25 (4): 548-554.
ObjectivesAcute kidney injury (AKI) is a serious complication after cardiac surgery and is associated with increased in-hospital deaths. Renal replacement therapy (RRT) is becoming a routine strategy for severe AKI. Our goal was to evaluate the risk factors for death and RRT dependence in patients with AKI after cardiac surgery.MethodsWe included 190 eligible adult patients who had AKI following cardiac surgery and who required RRT at our centre from November 2010 to March 2015. We collected preoperative, intraoperative, postoperative and RRT data for all patients.ResultsIn this cohort, 87 patients had successful RRT in the hospital, whereas 103 patients had RRT that failed (70 deaths and 33 cases of RRT dependence). The multivariable logistic analysis identified old age [odds ratio (OR): 1.042, 95% confidence interval (CI): 1.012-1.074; P = 0.011], serum uric acid (OR: 1.015, 95% CI: 1.003-1.031; P = 0.024), intraoperative concentrated red blood cell transfusions (OR: 1.144, 95% CI: 1.006-1.312; P = 0.041), postoperative low cardiac output syndrome (OR: 3.107, 95% CI: 1.179-8.190; P = 0.022) and multiple organ failure (OR: 5.786, 95% CI: 2.115-15.832; P = 0.001) as factors associated with a higher risk for RRT failure. The prediction model (-4.3 + 0.002 × preuric acid + 0.10 × concentrated red blood cells + 0.04 × age + 1.12 × [low cardiac output syndrome = 1] + 1.67 × [multiple organ failure = 1]) based on the multivariate analysis had statistically significant different incriminatory power with an area under the curve of 0.786.ConclusionsThe prediction model may serve as a simple, accurate tool for predicting in-hospital RRT failure for patients with AKI following cardiac surgery.© The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.
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