Diagnostic Accuracy of Simplified Prehospital Sepsis Screening Tools for Identifying Sepsis and Predicting 30-Day Mortality: A Retrospective Diagnostic Accuracy Study.

IF 4.3 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Clinical Epidemiology Pub Date : 2026-09-04 eCollection Date: 2026-01-01 DOI:10.2147/CLEP.S620744
Thongpitak Huabbangyang, Gawin Tiyawat, Nitiporn Puysopa, Thapanee Wattanasaringkarn, Jiratchaya Khunjan, Warinthorn Inthanon, Nattanicha Duangkaew, Chanathip Wanphen, Adisak Nithimathachoke
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引用次数: 0

Abstract

Background: Early recognition of sepsis in prehospital settings remains challenging because emergency medical services (EMS) clinicians must make rapid triage decisions using limited physiological information before hospital arrival. Several sepsis screening tools have been validated in emergency department settings; however, comparative evidence in prehospital populations remains limited.

Purpose: This study evaluated the diagnostic and prognostic performance of five simplified screening tools-mNEWS, qSOFA, mSIRS, mSOS, and MEWS-for identifying sepsis and predicting 30-day mortality in prehospital patients.

Methods: This retrospective diagnostic accuracy study included 268 adult patients (≥18 years) transported by Vajira Emergency Medical Service, Bangkok, Thailand, to Vajira Hospital between January 2018 and October 2024. Prehospital clinical parameters recorded by paramedics and emergency nurse practitioners were analyzed against the final hospital diagnosis of sepsis and 30-day in-hospital mortality. Predefined thresholds (mSOS ≥4, MEWS ≥5, mNEWS ≥5, qSOFA ≥2, and mSIRS ≥2) were used for the primary analyses. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AuROC), sensitivity, and specificity.

Results: Among 268 patients, MEWS demonstrated the highest discrimination for identifying sepsis (AuROC 0.84; sensitivity 64.9%; specificity 79.1%). mSOS (AuROC 0.83) and mSIRS (AuROC 0.82) demonstrated high sensitivity (>96%) but lower specificity (~60%), while mNEWS showed the highest sensitivity (99.3%) but poor specificity (47.0%). qSOFA demonstrated the lowest discrimination (AuROC 0.72). For predicting 30-day mortality, MEWS demonstrated the highest performance (AuROC 0.70; sensitivity 72.2%; specificity 64.5%), followed by mNEWS and mSOS (AuROC 0.69 each), whereas qSOFA (AuROC 0.64) and mSIRS (AuROC 0.60) demonstrated lower discrimination.

Conclusion: MEWS demonstrated the most balanced diagnostic performance for identifying sepsis and predicting 30-day mortality in prehospital patients. Highly sensitive tools may be useful for early screening, whereas MEWS may better support risk stratification. Further external validation is required before broader implementation.

简化院前败血症筛查工具诊断败血症和预测30天死亡率的准确性:一项回顾性诊断准确性研究
背景:院前脓毒症的早期识别仍然具有挑战性,因为紧急医疗服务(EMS)临床医生必须在医院到达之前使用有限的生理信息做出快速的分诊决定。几种败血症筛查工具已在急诊科得到验证;然而,院前人群的比较证据仍然有限。目的:本研究评估了5种简化筛查工具(mnews、qSOFA、mSIRS、mSOS和mews)在识别院前患者脓毒症和预测30天死亡率方面的诊断和预后表现。方法:本回顾性诊断准确性研究纳入了2018年1月至2024年10月期间由泰国曼谷Vajira急诊医疗服务中心送往Vajira医院的268名成年患者(≥18岁)。将护理人员和急诊护士记录的院前临床参数与败血症的最终医院诊断和30天住院死亡率进行分析。采用预定义阈值(mSOS≥4、MEWS≥5、mNEWS≥5、qSOFA≥2和mSIRS≥2)进行初步分析。使用受试者工作特征曲线下面积(AuROC)、敏感性和特异性评估诊断性能。结果:268例患者中,MEWS对脓毒症的鉴别能力最高(AuROC 0.84,敏感性64.9%,特异性79.1%)。mSOS (AuROC 0.83)和mSIRS (AuROC 0.82)灵敏度高(约为96%),特异性较低(约为60%),mNEWS灵敏度最高(99.3%),特异性较差(47.0%)。qSOFA的歧视程度最低(AuROC为0.72)。对于预测30天死亡率,MEWS表现出最高的性能(AuROC为0.70,敏感性为72.2%,特异性为64.5%),其次是mNEWS和mSOS (AuROC均为0.69),而qSOFA (AuROC为0.64)和mSIRS (AuROC为0.60)表现出较低的辨别能力。结论:MEWS在识别败血症和预测院前患者30天死亡率方面表现出最平衡的诊断性能。高度敏感的工具可能对早期筛查有用,而MEWS可能更好地支持风险分层。在更广泛的实现之前,需要进一步的外部验证。
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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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