C-Reactive Protein/Albumin Ratio Is Associated with Mortality in Patients with Moderate to Severe Traumatic Brain Injury

医学 格拉斯哥昏迷指数 置信区间 优势比 接收机工作特性 创伤性脑损伤 逻辑回归 内科学 曲线下面积 损伤严重程度评分 多元分析 外科 毒物控制 急诊医学 伤害预防 精神科
作者
Yifei Wang,Yu Gong,Cuiwei Du,Feng Xing,Peng Yang
出处
期刊:World Neurosurgery [Elsevier]
卷期号:173: e234-e240 被引量:1
标识
DOI:10.1016/j.wneu.2023.02.037
摘要

The C-reactive protein/albumin ratio (CAR), Glasgow coma scale score, and blood glucose level serve as reference values to evaluate the prognosis of critically ill patients. However, the prognostic significance of the admission serum CAR for patients with moderate to severe traumatic brain injury (TBI) has remained unclear. We examined the effect of the admission CAR on the outcomes of patients with moderate to severe TBI.The clinical data from 163 patients with moderate to severe TBI were collected. Before analysis, the patients' records were anonymized and de-identified. Multivariate logistic regression analyses were used to investigate the risk factors and construct a prognostic model of in-hospital mortality. The predictive value of different models was compared by evaluating the areas under the receiver operating characteristic curve.Of the 163 patients, those who had not survived (nonsurvivors, n = 34) had had a higher CAR than that of the survivors (3.8 vs. 2.6; P < 0.001). The results of multivariate logistic regression analysis indicated that the Glasgow coma scale score (odds ratio [OR], 0.430; P = 0.001), blood glucose (OR, 1.290; P = 0.017), and CAR (OR, 1.609; P = 0.036) were independent risk factors for mortality and were used to construct the prognostic model. The area under the receiver operating characteristic curve of the prognostic model was 0.922 (95% confidence interval, 0.875-0.970), higher than that for the CAR (P = 0.0409). We had screened 195 patients for inclusion in the present study and excluded 32 patients.The CAR can serve as an independent risk factor of mortality for patients with moderate to severe TBI. Incorporating CAR into a predictive model could contribute to efficiently predicting the prognosis of adults with moderate to severe TBI.

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