BioMed research international · 2020
The Predictive Value of Serum Uric Acid on Acute Kidney Injury following Traumatic Brain Injury.
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Wang Ruo Ran, He Min, Ou Xiao Feng, Xie Xiao Qi, Kang Yan
Аннотация
BACKGROUNDS: Acute kidney injury (AKI) is a prevalent nonneurological complication in patients with traumatic brain injury (TBI). We designed this study to explore the association between serum uric acid (SUA) level and the occurrence of AKI following TBI.
METHODS: This is a retrospective single-center study. A total of 479 patients admitted with TBI were included in this study. We utilized SUA and other risk factors for AKI to construct a predictive model by performing multivariate logistic regression. 374 patients and 105 patients were, respectively, divided into a training set and validation set. The predictive value of the single SUA and constructed model was evaluated by drawing a receiver operating characteristic (ROC) curve. AKI was diagnosed according to the KIDGO criteria.
RESULTS: 79 (21.12%) patients were diagnosed with AKI in the training cohort. The patients in the AKI group are older than those in the non-AKI group (p = 0.01). And the Glasgow Coma Scale (GCS) of the AKI group was lower than that of the non-AKI group (p < 0.001). In a multivariate logistic regression analysis, we found that heart rate (p = 0.041), shock (p = 0.018), serum creatinine (p < 0.001), and serum uric acid (SUA) (p < 0.001) were significant risk factors for AKI. Bivariate correlation analyses showed that serum creatinine was moderately positively correlated with SUA (r = 0.523, p < 0.001). Finally, the area under the receiver operating characteristic curve (AUC) of SUA for predicting AKI in the training set and validation set was 0.850 (0.805-0.895) and 0.869 (0.801-0.938), respectively.
CONCLUSIONS: SUA is an effective risk factor for AKI following TBI. Combining SUA with serum creatinine could more accurately identify TBI patients with high risk of developing AKI.
METHODS: This is a retrospective single-center study. A total of 479 patients admitted with TBI were included in this study. We utilized SUA and other risk factors for AKI to construct a predictive model by performing multivariate logistic regression. 374 patients and 105 patients were, respectively, divided into a training set and validation set. The predictive value of the single SUA and constructed model was evaluated by drawing a receiver operating characteristic (ROC) curve. AKI was diagnosed according to the KIDGO criteria.
RESULTS: 79 (21.12%) patients were diagnosed with AKI in the training cohort. The patients in the AKI group are older than those in the non-AKI group (p = 0.01). And the Glasgow Coma Scale (GCS) of the AKI group was lower than that of the non-AKI group (p < 0.001). In a multivariate logistic regression analysis, we found that heart rate (p = 0.041), shock (p = 0.018), serum creatinine (p < 0.001), and serum uric acid (SUA) (p < 0.001) were significant risk factors for AKI. Bivariate correlation analyses showed that serum creatinine was moderately positively correlated with SUA (r = 0.523, p < 0.001). Finally, the area under the receiver operating characteristic curve (AUC) of SUA for predicting AKI in the training set and validation set was 0.850 (0.805-0.895) and 0.869 (0.801-0.938), respectively.
CONCLUSIONS: SUA is an effective risk factor for AKI following TBI. Combining SUA with serum creatinine could more accurately identify TBI patients with high risk of developing AKI.