Nirula Ram, Talmor Daniel, Brasel Karen
Division of Trauma/Critical Care, Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA.
J Trauma. 2005 Jul;59(1):132-5. doi: 10.1097/01.ta.0000171465.80722.0c.
Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model.
Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models.
There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models.
We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.
识别与胸腹损伤相关的机动车碰撞（MVC）特征，将通过改善分诊和响应时间来推动自动碰撞通知系统（ACNS）的发展。我们的目标是确定MVC特征与胸腹创伤之间的关系，以建立一个躯干损伤概率模型。
回顾了1993年至2001年在国家汽车抽样系统内发生碰撞事故的驾驶员。使用多变量逻辑回归评估躯干损伤与MVC特征之间的关系。使用受试者工作特征曲线将该模型与当前的ACNS模型进行比较。
共有56466名驾驶员。年龄、弹射、制动、避让、速度、安全带使用情况、乘客侧碰撞、翻车以及车辆重量和类型与损伤相关（p < 0.05）。受试者工作特征曲线下面积（83.9）显著大于当前的ACNS模型。
我们已经开发出一种胸腹损伤概率模型，与ACNS一起使用时可能会改善患者分诊。
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