• Ruoran Wang, Min He, Xiao Feng Ou, Xiao Qi Xie, and Yan Kang.
• Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
• World Neurosurg. 2020 Sep 1; 141: e112-e117.

BackgroundA common non-neurologic complication after traumatic brain injury (TBI), acute kidney injury (AKI) is a risk factor of mortality. Some studies confirmed the predictive value of procalcitonin (PCT) on AKI in several clinical settings. We designed this study to explore the predictive value of PCT on AKI after TBI.MethodsWe retrospectively enrolled patients with TBI admitted to our hospital from February 2015 to June 2019. Multivariate logistic regression analysis was performed to find the risk factors of AKI and construct a predictive model for AKI. Receiver operating characteristics curves were drawn to compare the predictive value of PCT and the constructed model.ResultsA total of 214 patients were included in this study. The incidence of AKI after TBI was 25.70% in this study. Compared with the non-AKI group, the AKI group had higher age (P = 0.031), lower Glasgow Coma Scale (P < 0.001), and higher incidence of coagulopathy (P < 0.001) and shock (P < 0.001). Moreover, patients complicated with AKI had higher in-hospital mortality (P < 0.001) and worse 90-day outcome (P < 0.001). Multivariate logistic regression analysis indicated that age (P = 0.033), PCT (P = 0.002), serum chlorine (P = 0.011), and creatinine (P < 0.001) were independent risk factors of AKI. We constructed a predictive model using these 4 risk factors. The area under receiver operating characteristics curves of the predictive model was 0.928, which was significantly higher than that of a single PCT value (area under receiver operating characteristics curves = 0.833) (Z = 2.395, P < 0.05).ConclusionsPCT is valuable in predicting AKI after TBI. To avoid AKI after TBI, physicians can adjust treatment strategies according to the level of PCT.Copyright © 2020 Elsevier Inc. All rights reserved.

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