应用GAP、RTS和NTS模型预测多重创伤患者的死亡率

IF 0.2 Q4 EMERGENCY MEDICINE Trauma monthly Pub Date : 2021-10-19 DOI:10.30491/TM.2021.262592.1212
K. Amini, Soheila Abolghasemi Fakhri, Haniyeh Salehi, H. Bakhtavar, F. Rahmani
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引用次数: 1

摘要

背景:有几种创伤患者预后模型,本研究旨在评估年龄、收缩压(GAP)、修订创伤评分(RTS)和新创伤评分(NTS)来预测伊朗大不里士伊玛目雷扎医院多例创伤患者的死亡率。方法:对2018年7月至2019年8月544例多发创伤患者进行描述性分析研究。采用GAP、RTS和NTS模型收集变量数据。计算GAP、RTS和NTS评分,然后评估它们与医院预后的关系。结果:在本次研究中,入选样本中有31例患者死亡。RTS、NTS和GAP模型的医院生存率分界点(敏感性和特异性)分别为6.07(0.97和0.98)、5.59(0.94和0.99)和15.5(0.97和0.97)。采用Logistic回归检验确定GCS、GAP、RTS和NTS模型的效果。结果显示,RTS和NTS分数在决定生存机会方面的价值最高,其比值比(OR)分别为13.74和10.207。结论:考虑到RTS、GAP和NTS模型在确定患者生存率方面的高敏感性和特异性,这些模型在确定医院预后方面具有良好的预测价值。基于OR值,这些模型对患者预后的影响,RTS和NTS模型值较高。
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Mortality Prediction in Multiple Trauma Patients Using GAP, RTS and NTS Models
Background: There are several models for the prognosis of trauma patients and the present study aims to evaluate age, systolic blood pressure (GAP), revised trauma score (RTS), and new trauma score (NTS) to predict mortality rate in multiple trauma patients referring to Imam Reza Hospital, Tabriz, Iran.Methods: The present descriptive-analytical study was carried out on 544 multiple trauma patients during July 2018 to Aug 2019. GAP, RTS and NTS models were adopted to collect data on the variables. The GAP, RTS and NTS scores were calculated and their relationship with hospital outcome was then assessed.Result: During this study, 31 patients out of the selected sample died. The cut-off point (sensitivity and specificity) of RTS, NTS, and GAP models for hospital survival rates was equal to 6.07 (0.97 and 0.98), 5.59 (0.94 and 0.99), and 15.5 (0.97 and 0.97), respectively. Logistic regression test was run to determine the effects of GCS, GAP, RTS, and NTS models. The results showed that the RTS and NTS scores had the highest value in determining the chances of survival, with the respective odds ratios (OR) of 13.74 and 10.207.Conclusion: Considering the high sensitivity and specificity of RTS, GAP, and NTS models in determining patient survival rates, these models have good predictive value in determining hospital outcome. With regard to the effect of these models on the patient outcome based on OR values, RTS and NTS model showed high values.
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Trauma monthly
Trauma monthly EMERGENCY MEDICINE-
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