Ruoran Wang1, Min He1, Xiaofeng Ou1, Xiaoqi Xie1, Yan Kang2. 1. Department of Intensive Care Unit, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China. 2. Department of Intensive Care Unit, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China. Electronic address: kangyan@scu.edu.cn.
Abstract
OBJECTIVES: The C-reactive protein/albumin ratio (CAR), a novel inflammation-based index, has been proved useful in predicting outcome of various diseases. We designed this study to explore the prognostic value of CAR in patients with traumatic brain injury (TBI). PATIENTS AND METHODS: We retrospectively included 151 patients diagnosed with TBI and collected related clinical and laboratory data. Univariate and multivariate logistic regression were conducted to find independent risk factors of mortality. Then, we incorporated CAR into prognostic model and drew receiver operating characteristic (ROC) curve of models. Finally, we compared the predictive value of different models by evaluating the area under the receiver operating characteristic curves (AUC). RESULTS: In this study, a total of 54 patients had poor survival outcome with mortality rate of 35.8 %. Results of multivariate analysis showed that GCS score in admission (OR 0.700, 95 %Cl 0.570-0.860, p=0.001), acute kidney injury (AKI) (OR 3.952, 95Cl 1.631-9.577, p=0.002) and CAR (OR 1.202, 95Cl 1.039-1.390, p=0.013) were independently associated with in-hospital mortality. The AUC value of predictive model composed of the above three factors was higher than GCS or CAR alone. CONCLUSION: CAR is an independent risk factor of mortality in patients with TBI. Incorporating CAR into predictive model could increase the value in predicting outcome of TBI patients.
OBJECTIVES: The C-reactive protein/albumin ratio (CAR), a novel inflammation-based index, has been proved useful in predicting outcome of various diseases. We designed this study to explore the prognostic value of CAR in patients with traumatic brain injury (TBI). PATIENTS AND METHODS: We retrospectively included 151 patients diagnosed with TBI and collected related clinical and laboratory data. Univariate and multivariate logistic regression were conducted to find independent risk factors of mortality. Then, we incorporated CAR into prognostic model and drew receiver operating characteristic (ROC) curve of models. Finally, we compared the predictive value of different models by evaluating the area under the receiver operating characteristic curves (AUC). RESULTS: In this study, a total of 54 patients had poor survival outcome with mortality rate of 35.8 %. Results of multivariate analysis showed that GCS score in admission (OR 0.700, 95 %Cl 0.570-0.860, p=0.001), acute kidney injury (AKI) (OR 3.952, 95Cl 1.631-9.577, p=0.002) and CAR (OR 1.202, 95Cl 1.039-1.390, p=0.013) were independently associated with in-hospital mortality. The AUC value of predictive model composed of the above three factors was higher than GCS or CAR alone. CONCLUSION:CAR is an independent risk factor of mortality in patients with TBI. Incorporating CAR into predictive model could increase the value in predicting outcome of TBI patients.
Authors: Jacob E Bernstein; Jonathan D Browne; Paras Savla; James Wiginton; Tye Patchana; Dan E Miulli; Margaret Rose Wacker; Jason Duong Journal: Cureus Date: 2021-01-10
Authors: M Karen Newell-Rogers; Amanda Duong; Rizwan Nazarali; Richard P Tobin; Susannah K Rogers; Lee A Shapiro Journal: Int J Mol Sci Date: 2022-08-30 Impact factor: 6.208