Baik Dongyup, Yeom Seok-Ran, Park Sung-Wook, Cho Youngmo, Yang Wook Tae, Kwon Hoon, Lee Jae Il, Ko Jun-Kyeung, Choi Hyuk Jin, Huh Up, Goh Tae Sik, Song Chan-Hee, Hwangbo Lee, Wang Il Jae
Department of Emergency Medicine, School of Medicine, Pusan National University and Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea.
Department of Radiology, Biomedical Research Institute, Pusan National University Department of Radiology, Busan 49241, Republic of Korea.
Emerg Med Int. 2022 Oct 15;2022:7219812. doi: 10.1155/2022/7219812. eCollection 2022.
Rotational thrombelastometry (ROTEM) has been used to evaluate the coagulation state, predict transfusion, and optimize hemostatic management in trauma patients. However, there were limited studies on whether the prediction value could be improved by adding the ROTEM parameter to the prediction model for in-hospital mortality and massive transfusion (MT) in trauma patients.
This study assessed whether ROTEM data could improve the MT prediction model.
This was a single-center, retrospective study. Patients who presented to the trauma center and underwent ROTEM between 2016 and 2020 were included. The primary and secondary outcomes were massive transfusions and in-hospital mortality, respectively. We constructed two models using multivariate logistic regression with backward conditional stepwise elimination (Model 1: without the ROTEM parameter and Model 2: with the ROTEM parameter). The area under the receiver operating characteristic curve (AUROC) was calculated to assess the predictive ability of the models.
In total, 969 patients were included; 196 (20.2%) received MT. The in-hospital mortality rate was 14.1%. For MT, the AUROC was 0.854 (95% confidence interval [CI], 0.825-0.883) and 0.860 (95% CI, 0.832-0.888) for Model 1 and 2, respectively. For in-hospital mortality, the AUROC was 0.886 (95% CI, 0.857-0.915) and 0.889 (95% CI, 0.861-0.918) for models 1 and 2, respectively. The AUROC values for models 1 and 2 were not statistically different for either MT or in-hospital mortality.
We found that the addition of the ROTEM parameter did not significantly improve the predictive power of MT and in-hospital mortality in trauma patients.
旋转血栓弹力图（ROTEM）已被用于评估创伤患者的凝血状态、预测输血情况并优化止血管理。然而，关于在创伤患者院内死亡率和大量输血（MT）预测模型中加入ROTEM参数是否能提高预测价值的研究有限。
本研究评估ROTEM数据是否能改进大量输血预测模型。
这是一项单中心回顾性研究。纳入2016年至2020年间前往创伤中心并接受ROTEM检测的患者。主要和次要结局分别为大量输血和院内死亡率。我们使用多因素逻辑回归和向后条件逐步淘汰法构建了两个模型（模型1：不包含ROTEM参数；模型2：包含ROTEM参数）。计算受试者操作特征曲线下面积（AUROC）以评估模型的预测能力。
共纳入969例患者；196例（20.2%）接受了大量输血。院内死亡率为14.1%。对于大量输血，模型1和模型2的AUROC分别为0.854（95%置信区间[CI]，0.825 - 0.883）和0.860（95%CI，0.832 - 0.888）。对于院内死亡率，模型1和模型2的AUROC分别为0.886（95%CI，0.857 - 0.915）和0.889（95%CI，0.861 - 0.918）。模型1和模型2的AUROC值在大量输血或院内死亡率方面无统计学差异。
我们发现加入ROTEM参数并未显著提高创伤患者大量输血和院内死亡率的预测能力。
