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院前创伤分诊工具对高危或危及生命的院前创伤患者24小时内复苏干预的预测性能。

Predictive performance of prehospital trauma triage tools for resuscitative interventions within 24 hours in high-risk or life-threatening prehospital trauma patients.

作者信息

Jenpanitpong Chetsadakon, Yuksen Chaiyaporn, Trakulsrichai Satariya, Sricharoen Pungkava, Leela-Amornsin Sittichok, Savatmongkorngul Sorravit, Sanguanwit Pitsucha

机构信息

Division of Paramedicine, Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, 10400, Thailand.

Division of Emergency Medicine, Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, 10400, Thailand.

出版信息

BMC Emerg Med. 2025 Feb 20;25(1):26. doi: 10.1186/s12873-025-01188-x.

DOI:10.1186/s12873-025-01188-x
PMID:39979975
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11841352/
Abstract

INTRODUCTION

Several prehospital trauma triage tools have been recently developed, but no standardized tools currently exist to identify trauma patients at risk of requiring resuscitative interventions (RIs) within the first 24 h post-injury and to prioritize their transport to high-level trauma facilities.

METHODS

This prognostic study employed a retrospective cohort design to evaluate the predictive performance of the Triage Revised Score (T-RTS), Glasgow Coma Scale, Age, and Systolic Blood Pressure Score (GAP), Mechanism, Glasgow Coma Scale, Age, and Systolic Blood Pressure Score (MGAP), National Early Warning Score 2 (NEWS-2), Shock Index (SI), and Reverse Shock Index multiplied by Glasgow Coma Scale (rSIG) in predicting the need for RIs within 24 h. Data was retrieved from the electronic medical records of Ramathibodi Hospital, and the study included patients aged ≥ 15 years who were categorized as high-risk or life-threatening and subsequently transported to the emergency department. We used Area Under the Receiver Operating Characteristic (AUROC) curve and calibration plots to assess the performance of prehospital trauma triage tools.

RESULTS

There were 440 traumatic injury patients enrolled in the study, with 44 (10%) receiving RIs. T-RTS, GAP, MGAP, and NEWS-2 demonstrate good discriminative and predictive performance for RIs within 24 h after an injury (AUROC of 0.969, 0.949, 0.971, and 0.929, respectively, with the O:E ratio of 1). With the predefined standard cut-off values, the GAP score of less than 19 results in the highest accuracy for ruling out patients who do not need RIs (Specificity = 94.4% and NPV = 94.1%, p-value < 0.001).

CONCLUSIONS

Several commonly used prehospital trauma triage tools demonstrate good predictive abilities for identifying the need for RIs. Among these, the GAP score with a threshold value of 19 serves as an optimal tool for identifying patients who require transfer to high-level trauma facilities.

摘要

引言

最近已经开发了几种院前创伤分诊工具,但目前尚无标准化工具来识别受伤后24小时内有需要进行复苏干预(RI)风险的创伤患者,并确定将他们转运至高级创伤救治机构的优先顺序。

方法

这项预后研究采用回顾性队列设计,以评估分诊修订评分(T-RTS)、格拉斯哥昏迷量表、年龄和收缩压评分(GAP)、机制、格拉斯哥昏迷量表、年龄和收缩压评分(MGAP)、国家早期预警评分2(NEWS-2)、休克指数(SI)以及格拉斯哥昏迷量表乘以反向休克指数(rSIG)在预测24小时内是否需要进行复苏干预方面的预测性能。数据从拉玛蒂博迪医院的电子病历中获取,该研究纳入了年龄≥15岁、被归类为高危或危及生命并随后被转运至急诊科的患者。我们使用受试者操作特征曲线下面积(AUROC)和校准图来评估院前创伤分诊工具的性能。

结果

该研究共纳入440例创伤性损伤患者,其中44例(10%)接受了复苏干预。T-RTS、GAP、MGAP和NEWS-2在受伤后24小时内对复苏干预显示出良好的鉴别和预测性能(AUROC分别为0.969、0.949、0.971和0.929,O:E比值为1)。根据预先定义的标准临界值,GAP评分低于19对排除不需要复苏干预的患者具有最高的准确性(特异性=94.4%,阴性预测值=94.1%,p值<0.001)。

结论

几种常用院前创伤分诊工具在识别是否需要进行复苏干预方面显示出良好的预测能力。其中,阈值为19的GAP评分是识别需要转至高级创伤救治机构患者的最佳工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/fda9220f318e/12873_2025_1188_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/c425a5a26f42/12873_2025_1188_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/80a3c680582c/12873_2025_1188_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/1441d9b866e4/12873_2025_1188_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/fda9220f318e/12873_2025_1188_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/c425a5a26f42/12873_2025_1188_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/80a3c680582c/12873_2025_1188_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/1441d9b866e4/12873_2025_1188_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51c/11841352/fda9220f318e/12873_2025_1188_Fig4_HTML.jpg

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