Designing a Model to Predict the Mortality in Multiple Trauma Patients due to Traffic Accidents

IF 0.4 4区 医学
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引用次数: 0

Abstract

Background: It is of prime importance to manage trauma patients in the early hours and use easy trauma severity scoring systems to make decisions and evaluate patient prognosis. Objectives: The present study aimed to design a predictive model of the mortality of multi-trauma patients due to traffic accidents. Methods: This cross-sectional analytical study was performed on 600 patients who suffered from multi-trauma caused by traffic accidents from December 2019 to September 2021. Collected data included age, sex, vital signs, trauma mechanism, involved vehicle in the accident, accident location, and hospital outcome. Results: In this study, 600 multi-trauma cases caused by traffic accidents were evaluated. Among the significant variables included in the regression model, age, Mean Arterial Pressure (MAP), Glasgow Coma Scale (GCS), AVPU (Alert, Verbal response, Pain response, Unresponsive), and vehicle versus fixed objects (in Vehicle 2) in the presence of other variables in the model, significantly predicted patient outcomes. Therefore, with the other variables being constant, one unit increase in the age variable increases the probability of death by 1.04 times, one unit increase in the score of the two variables of MAP and GCS, and also the transfer of trauma mechanism from the fixed object to the vehicle reduces death by 0.92, 0.62, and 0.10 times, respectively. In the AVPU variable, the transition from Alert to Verbal, the transition from Verbal to Pain, and the transition from Pain to Unresponsive increases the probability of death by 32, 104, and 567, respectively. Conclusion: In this study, AVPU, age, MAP, primary GCS, and trauma mechanism due to hitting a vehicle with a fixed object had significantly the highest predictive power of hospital mortality in patients with multiple trauma due to traffic accidents, respectively. It is suggested that further studies be performed to replace the AVPU variable with GCS in the newly designed formulas for calculating the severity of trauma to simplify these scores.
设计一个模型来预测交通事故导致的多发性创伤患者的死亡率
背景:最重要的是在早期对创伤患者进行管理,并使用简便的创伤严重程度评分系统来做出决定和评估患者的预后。研究目的本研究旨在设计一个预测交通事故导致的多发性创伤患者死亡率的模型。方法:本横断面分析研究的对象是 2019 年 12 月至 2021 年 9 月期间因交通事故造成的 600 名多发性创伤患者。收集的数据包括年龄、性别、生命体征、创伤机制、事故车辆、事故地点和住院结果。研究结果本研究评估了 600 例因交通事故造成的多发创伤病例。在回归模型中包含的重要变量中,年龄、平均动脉压(MAP)、格拉斯哥昏迷量表(GCS)、AVPU(警觉、语言反应、疼痛反应、无反应)以及车辆与固定物体(在车辆 2 中)在模型中存在其他变量的情况下,可显著预测患者的预后。因此,在其他变量不变的情况下,年龄变量每增加一个单位,死亡概率就会增加 1.04 倍,MAP 和 GCS 两个变量的得分每增加一个单位,以及将创伤机制从固定物体转移到车辆上,死亡概率就会分别降低 0.92 倍、0.62 倍和 0.10 倍。在 AVPU 变量中,从 "警觉 "到 "言语"、从 "言语 "到 "疼痛 "以及从 "疼痛 "到 "无反应 "分别会使死亡概率增加 32、104 和 567 倍。结论在本研究中,AVPU、年龄、MAP、主要 GCS 和因固定物体撞车导致的创伤机制分别对交通事故导致的多发创伤患者的住院死亡率具有显著的最高预测能力。建议开展进一步研究,在新设计的创伤严重程度计算公式中用 GCS 取代 AVPU 变量,以简化这些评分。
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来源期刊
Iranian Red Crescent Medical Journal
Iranian Red Crescent Medical Journal 医学-医学:内科
自引率
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期刊介绍: The IRANIAN RED CRESCENT MEDICAL JOURNAL is an international, English language, peer-reviewed journal dealing with general Medicine and Surgery, Disaster Medicine and Health Policy. It is an official Journal of the Iranian Hospital Dubai and is published monthly. The Iranian Red Crescent Medical Journal aims at publishing the high quality materials, both clinical and scientific, on all aspects of Medicine and Surgery
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