Risk model for deaths and renal replacement therapy dependence in patients with acute kidney injury after cardiac surgery

Abstract

Objectives: Acute 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.

Methods: We 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.

Results: In 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.

Conclusions: The prediction model may serve as a simple, accurate tool for predicting in-hospital RRT failure for patients with AKI following cardiac surgery.

Keywords: Acute kidney injury; Cardiac surgery; Mortality; Renal replacement therapy; Risk factor.