Kim Sol Bi, Park Youngjoon, Ahn Ju Won, Sim Jeongmin, Park Jeongman, Kim Yu Jin, Hwang So Jung, Sung Kyoung Su, Lim Jaejoon
Department of Neurosurgery, Bundang CHA Medical Center, CHA University, Yatap-dong 59, Seongnam 13496, Korea.
Department of Biomedical Science, College of Life Science, CHA University, Seongnam 13488, Korea.
J Clin Med. 2022 Jun 5;11(11):3220. doi: 10.3390/jcm11113220.
Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accurately. In this study, we created a model that can predict the survival of patients with TBI by adding hematologic parameters along with existing non-hematologic parameters. The best-fitting model was created using the Akaike information criterion (AIC), and hematologic factors including preoperative hematocrit, preoperative C-reactive protein (CRP), postoperative white blood cell (WBC) count, and postoperative hemoglobin were selected to predict the prognosis. Among several prediction models, the model that included age, Glasgow Coma Scale, Injury Severity Score, preoperative hematocrit, preoperative CRP, postoperative WBC count, postoperative hemoglobin, and postoperative CRP showed the highest area under the curve and the lowest corrected AIC for a finite sample size. Our study showed a new prediction model for mortality in patients with TBI using non-hematologic and hematologic parameters. This prediction model could be useful for the management of patients with TBI.
创伤性脑损伤（TBI）频繁发生，需要手术治疗的急性TBI与患者生存密切相关。预测TBI患者预后的模型未考虑患者状态的各种因素；因此，更准确地预测预后很困难。在本研究中，我们通过将血液学参数与现有的非血液学参数相加，创建了一个可以预测TBI患者生存情况的模型。使用赤池信息准则（AIC）创建了最佳拟合模型，并选择包括术前血细胞比容、术前C反应蛋白（CRP）、术后白细胞（WBC）计数和术后血红蛋白在内的血液学因素来预测预后。在几种预测模型中，包含年龄、格拉斯哥昏迷量表、损伤严重程度评分、术前血细胞比容、术前CRP、术后WBC计数、术后血红蛋白和术后CRP的模型在有限样本量下显示出最高的曲线下面积和最低的校正AIC。我们的研究展示了一种使用非血液学和血液学参数预测TBI患者死亡率的新模型。这种预测模型可能对TBI患者的管理有用。
