Kenarangi Taiebe, Rahmani Farzad, Yazdani Ali, Ahmadi Ghazaleh Doustkhah, Lotfi Morteza, Khalaj Toktam Akbari
Department of Biostatistics and Epidemiology, Faculty of Statistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
Department of Statistics, Emergency Medical Services, Mashhad University of Medical Sciences, Mashhad, Iran.
Heliyon. 2024 Aug 8;10(16):e36004. doi: 10.1016/j.heliyon.2024.e36004. eCollection 2024 Aug 30.
There are several trauma scoring systems with varying levels of accuracy and reliability that have been developed to predict and classify mortality in trauma patients in the hospital admission. Considering the importance of the country's emergency organization and the World Health Organization in the category of traffic accidents, we used this information in the study. The objective of this study is to evaluate and compare the predictive power of three scoring systems (R-GAP, GAP, and NTS) on traffic accident injuries.
In an analytical cross-sectional study, all the data related to the mission of traffic accidents at the pre-hospital emergency management of Mashhad University of Medical Sciences in 2022 were extracted from the automation system, and the outcome of the patients in the hospital was recorded from the integrated hospital system. Then, GAP, R-GAP, and New Trauma Scores (NTS) were calculated, and their results were compared using ROC curve and logistic regression.
In this study, 47,971 injuries from traffic accidents were evaluated. Their average age was 30.16 ± 10.93 years. R-GAP showed negligible difference than GAP and NTS scores (the area under the curve equals 0.904, 0.935, and 0.884, respectively), and the average scores of R-GAP, GAP, and NTS are equal to 22.45/45 ± 1/9, 22.25 ± 1.5, and 22.49 ± 1.3, respectively. Injury severity based on R-GAP, GAP, and NTS scores was mild in most patients. The effect of these models on the patient outcome based on OR values, R-GAP, GAP, and NTS models showed high values. All analysis was performed in SPSS 26.
According to the study results, it seems that R-GAP, GAP, and NTS, have the highest power to predict death in traffic accident injuries. It is recommended to include these points in the electronic file of the pre-hospital emergency for the injured. Also, the severity and outcome of the patient can be predicted by these scores, which play an important role in the triage of the injured and determining the appropriate treatment center.
为预测和分类创伤患者入院时的死亡率，已开发出几种准确性和可靠性各不相同的创伤评分系统。考虑到该国应急组织和世界卫生组织在交通事故类别中的重要性，我们在研究中使用了这些信息。本研究的目的是评估和比较三种评分系统（R-GAP、GAP和NTS）对交通事故损伤的预测能力。
在一项分析性横断面研究中，从自动化系统中提取了2022年马什哈德医科大学院前急救管理中与交通事故任务相关的所有数据，并从综合医院系统中记录了患者在医院的结局。然后，计算GAP、R-GAP和新创伤评分（NTS），并使用ROC曲线和逻辑回归比较其结果。
在本研究中，评估了47971例交通事故损伤。他们的平均年龄为30.16±10.93岁。R-GAP与GAP和NTS评分的差异可忽略不计（曲线下面积分别为0.904、0.935和0.884），R-GAP、GAP和NTS的平均评分分别为22.45/45±1/9、22.25±1.5和22.49±1.3。大多数患者基于R-GAP、GAP和NTS评分的损伤严重程度为轻度。基于OR值，这些模型对患者结局的影响，R-GAP、GAP和NTS模型显示出较高的值。所有分析均在SPSS 26中进行。
根据研究结果，似乎R-GAP、GAP和NTS在预测交通事故损伤死亡方面具有最高的能力。建议将这些要点纳入受伤者院前急救的电子文件中。此外，这些评分可以预测患者情况的严重程度和结局，这在受伤者的分诊和确定合适的治疗中心方面发挥着重要作用。
