• Dmytro Korenkevych, Tezcan Ozrazgat-Baslanti, Paul Thottakkara, Charles E Hobson, Panos Pardalos, Petar Momcilovic, and Azra Bihorac.
• Center for Applied Optimization, Industrial and Systems Engineering, University of Florida, Gainesville, FL.
• Ann. Surg. 2016 Jun 1; 263 (6): 1219-1227.

ObjectiveCalculate mortality risk that accounts for both severity and recovery of postoperative kidney dysfunction using the pattern of longitudinal change in creatinine.BackgroundAlthough the importance of renal recovery after acute kidney injury (AKI) is increasingly recognized, the complex association that accounts for longitudinal creatinine changes and mortality is not fully described.MethodsWe used routinely collected clinical information for 46,299 adult patients undergoing major surgery to develop a multivariable probabilistic model optimized for nonlinearity of serum creatinine time series that calculates the risk function for 90-day mortality. We performed a 70/30 cross validation analysis to assess the accuracy of the model.ResultsAll creatinine time series exhibited nonlinear risk function in relation to 90-day mortality and their addition to other clinical factors improved the model discrimination. For any given severity of AKI, patients with complete renal recovery, as manifested by the return of the discharge creatinine to the baseline value, experienced a significant decrease in the odds of dying within 90 days of admission compared with patients with partial recovery. Yet, for any severity of AKI, even complete renal recovery did not entirely mitigate the increased odds of dying, as patients with mild AKI and complete renal recovery still had significantly increased odds for dying compared with patients without AKI [odds ratio: 1.48 (95% confidence interval: 1.30-1.68)].ConclusionsWe demonstrate the nonlinear relationship between both severity and recovery of renal dysfunction and 90-day mortality after major surgery. We have developed an easily applicable computer algorithm that calculates this complex relationship.

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