Department of Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Department of Surgery, Kamuzu Central Hospital, Lilongwe, Malawi.
Injury. 2019 Sep;50(9):1552-1557. doi: 10.1016/j.injury.2019.07.004. Epub 2019 Jul 9.
Globally, traumatic injury is a leading cause of morbidity and mortality in low-income countries. Current tools for predicting trauma-associated mortality are often not applicable in low-resource environments due to a lack of diagnostic adjuncts. This study sought to derive and validate a model for predicting mortality that requires only a history and physical exam.
We conducted a retrospective analysis of all patients recorded in the Kamuzu Central Hospital trauma surveillance registry in Lilongwe, Malawi from 2011 through 2014. Using statistical randomization, 80% of patients were used for derivation and 20% were used for validation. Logistic regression modeling was used to derive factors associated with mortality and the Malawi Trauma Score (MTS) was constructed. The model fitness was tested.
62,354 patients are included. Patients are young (mean age 23.0, SD 15.9 years) with a male preponderance (72%). Overall mortality is 1.8%. The MTS is tabulated based on initial mental status (alert, responds to voice, responds only to pain or worse), anatomical location of the most severe injury, the presence or absence of a radial pulse on examination, age, and sex. The score range is 2-32. A mental status exam of only responding to pain or worse, head injury, the absence of a radial pulse, extremes of age, and male sex all conferred a higher probability of mortality. The ROC area under the curve for the derivation cohort and validation cohort were 0.83 (95% CI 0.78, 0.87) and 0.83 (95% CI 0.75, 0.92), respectively. A MTS of 25 confers a 50% probability of death.
The MTS provides a reliable tool for trauma triage in sub-Saharan Africa and helps risk stratify patient populations. Unlike other models previously developed, its strength is its utility in virtually any environment, while reliably predicting injury- associated mortality.
在全球范围内,创伤是低收入国家发病率和死亡率的主要原因。由于缺乏诊断辅助手段,目前用于预测与创伤相关死亡率的工具在资源匮乏的环境中往往不适用。本研究旨在开发和验证一种仅需要病史和体格检查即可预测死亡率的模型。
我们对 2011 年至 2014 年期间在马拉维利隆圭的卡姆祖中央医院创伤监测登记处记录的所有患者进行了回顾性分析。使用统计随机化,80%的患者用于推导,20%用于验证。使用逻辑回归建模来推导与死亡率相关的因素,并构建马拉维创伤评分(MTS)。测试了模型的拟合度。
共纳入 62354 例患者。患者年龄较轻(平均年龄 23.0,SD 15.9 岁),男性居多(72%)。总体死亡率为 1.8%。MTS 根据初始精神状态(警觉、对声音有反应、仅对疼痛或更严重有反应)、最严重损伤的解剖位置、体格检查时是否存在桡动脉脉搏、年龄和性别进行编制。评分范围为 2-32。只有对疼痛或更严重、头部损伤、桡动脉脉搏缺失、年龄极端和男性的精神状态检查都预示着更高的死亡率。推导队列和验证队列的 ROC 曲线下面积分别为 0.83(95%CI 0.78,0.87)和 0.83(95%CI 0.75,0.92)。MTS 得分为 25 分预示着死亡的概率为 50%。
MTS 为撒哈拉以南非洲的创伤分诊提供了一种可靠的工具,有助于对患者人群进行风险分层。与以前开发的其他模型不同,其优势在于它在几乎任何环境中都具有实用性,同时能够可靠地预测与损伤相关的死亡率。