Comparison of GAP, R-GAP, and new trauma score (NTS) systems in predicting mortality of traffic accidents that injure hospitals at Mashhad University of medical sciences

• 發表在: Heliyon
• Main Authors: Taiebe Kenarangi, Farzad Rahmani, Ali Yazdani, Ghazaleh Doustkhah Ahmadi, Morteza Lotfi, Toktam Akbari Khalaj
• 格式: Article
• 語言: 英语
• 出版: Elsevier 2024-08-01
• 主題: Pre-hospital emergency; Outcome; Mortality; Accidents
• 在線閱讀: http://www.sciencedirect.com/science/article/pii/S240584402412035X

Background: 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. Methods: 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. Results: 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. Conclusion: 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.