Current state of trauma care in China, tools to predict death and ICU admission after arrival to hospital
Current state of trauma care in China, tools to predict death and ICU admission after arrival to hospital
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中国创伤护理现状、预测死亡和入院后入住 ICU 的工具
DOI：
10.1016/j.injury.2015.06.002
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发表时间：
2015-09-01
影响因子：
2.5
通讯作者：
Jiang, Baoguo
中科院分区：
文献类型：
--
作者：
Kong, Guilan;Yin, Xiaofeng;Jiang, Baoguo
背景：在中国，一个全国性的急救系统负责院前急救服务，它采用就近原则将创伤患者送往最近的医院。然而，许多重伤患者被送往没有能力治疗严重创伤的低级医院。因此，需要在急诊科（ED）识别那些院内死亡或入住重症监护病房（ICU）概率高的患者，以优化医院资源利用并改善患者预后。本研究的目的是开发一种计算机化工具，以帮助急诊科医生预测创伤患者入院后的院内死亡和入住ICU情况。
方法：我们回顾了华北开滦医院直接送往急诊科的1299例创伤患者样本。在排除数据录入不完整的病例后，1195例患者的信息用于分析。主要结局是导致院内死亡或入住ICU的严重创伤。我们提议在决策支持系统（DSS）中采用一种互补方法，将院前指数（PHI）、创伤指数（TI）和格拉斯哥昏迷评分（GCS）相结合来评估创伤并预测院内死亡和入住ICU情况。使用敏感性、特异性、过度分诊率和分诊不足率作为衡量指标，比较DSS与三种评分工具的系统性能。
结果：在1195例患者中，30例（2.5%）有严重创伤。所提出的DSS在所有四种研究工具中显示出最佳敏感性（66.7%；95%置信区间：49.8 - 83.6%）。TI（敏感性50.0%，95%置信区间：32.2 - 67.8%）的表现略优于GCS（敏感性46.7%，95%置信区间：28.9 - 64.5%），而TI和GCS都优于PHI（敏感性30.0%，95%置信区间：13.5 - 46.5%）。DSS与三种现有评分工具之间的性能差异具有统计学意义。
结论：所提出的DSS优于现有的创伤评分系统。它有很大潜力帮助急诊科医生识别严重创伤，优化医院资源利用，并为院内死亡和入住ICU可能性大的创伤患者推荐合适的分诊和治疗策略。（C）2015年由爱思唯尔有限公司出版
Background: In China, a nationwide emergency system takes charge of pre-hospital emergency services, and it adopts a proximity principle to send trauma patients to the nearest hospitals. However, many severely injured patients have been sent to low level hospitals with no capability to treat severe trauma. Thus those patients with high probability of in-hospital death or intensive care unit (ICU) admission need to be identified in the emergency department (ED) for optimal utilisation of hospital resources and better patient outcomes. The purpose of the study was to develop a computerised tool to aid ED physicians' prediction of in-hospital death and ICU admission for trauma patients after arrival to hospital.Methods: We reviewed a sample of 1,299 trauma patients who had been directly sent to the ED at Kailuan Hospital, North China. After excluding those cases with incomplete data entry, information of 1,195 patients was employed for analysis. The primary outcome was severe trauma that either resulted in death in hospital or in ICU admission. We proposed to use a complementary approach to combine the Pre-Hospital Index (PHI), the Trauma Index (TI), and the Glasgow Coma Score (GCS) in a decision support system (DSS) to assess trauma and predict in-hospital death and ICU admission. The sensitivity, specificity, over-triage rate, and under-triage rate were used as measurements to compare system performances of the DSS with the three scoring tools.Results: Among the 1,195 patients, 30 (2.5%) had severe trauma. The proposed DSS showed the best sensitivity (66.7%; 95% CI: 49.8-83.6%) among all the four studied tools. The TI (sensitivity 50.0%, 95% CI: 32.2-67.8%) performed slightly better than the GCS (sensitivity 46.7%, 95% CI: 28.9-64.5%), while both the TI and GCS performed better than the PHI (sensitivity 30.0%, 95% CI: 13.5-46.5%). The performance differences between the DSS and the three extant scoring tools were statistically significant.Conclusions: The proposed DSS outperformed the extant trauma scoring systems. It has a strong potential to help ED physicians identify severe trauma, optimally utilise hospital resources, and recommend appropriate triage and treatment strategies for trauma patients that have strong possibilities for in-hospital death and ICU admission. (C) 2015 Published by Elsevier Ltd.