■已经开发了几种具有不同准确性和可靠性水平的创伤评分系统,用于预测和分类住院中创伤患者的死亡率。考虑到国家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)关于交通事故伤害。
■在分析性横断面研究中,2022年马什哈德医科大学院前应急管理中与交通事故任务相关的所有数据均从自动化系统中提取,并从综合医院系统记录患者在医院的结局。然后,GAP,R-GAP,并计算了新的创伤分数(NTS),并使用ROC曲线和logistic回归对其结果进行比较。
■在这项研究中,评估了47,971起交通事故造成的伤害。他们的平均年龄为30.16±10.93岁。R-GAP与GAP和NTS评分相比差异可忽略不计(曲线下面积分别等于0.904、0.935和0.884),以及R-GAP的平均分数,GAP,和NTS分别等于22.45/45±1/9、22.25±1.5和22.49±1.3。基于R-GAP的损伤严重程度,GAP,大多数患者的NTS评分较轻。这些模型对基于OR值的患者预后的影响,R-GAP,GAP,和NTS模型显示出较高的值。所有分析均在SPSS26中进行。
■根据研究结果,看起来R-GAP,GAP,和NTS,有最高的权力来预测交通事故中的死亡伤害。建议将这些要点包括在伤员院前急救的电子文件中。此外,这些评分可以预测患者的严重程度和结果,这在伤员的分诊和确定合适的治疗中心中起着重要作用。
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.