• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

院前环境中感染和脓毒症的流行病学和患者预测因素。

Epidemiology and patient predictors of infection and sepsis in the prehospital setting.

机构信息

Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, Suite 425, Toronto, ON, M5T 3M6, Canada.

Rescu, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.

出版信息

Intensive Care Med. 2020 Jul;46(7):1394-1403. doi: 10.1007/s00134-020-06093-4. Epub 2020 May 28.

DOI:10.1007/s00134-020-06093-4
PMID:32468084
Abstract

PURPOSE

Paramedics are often the first healthcare contact for patients with infection and sepsis and may identify them earlier with improved knowledge of the clinical signs and symptoms that identify patients at higher risk.

METHODS

A 1-year (April 2015 and March 2016) cohort of all adult patients transported by EMS in the province of Alberta, Canada, was linked to hospital administrative databases. The main outcomes were infection, or sepsis diagnosis among patients with infection, in the Emergency Department. We estimated the probability of these outcomes, conditional on signs and symptoms that are commonly available to paramedics.

RESULTS

Among 131,745 patients transported by EMS, the prevalence of infection was 9.7% and sepsis was 2.1%. The in-hospital mortality rate for patients with sepsis was 28%. The majority (62%) of patients with infections were classified by one of three dispatch categories ("breathing problems," "sick patient," or "inter-facility transfer"), and the probability of infection diagnosis was 17-20% for patients within these categories. Patients with elevated temperature measurements had the highest probability for infection diagnosis, but altered Glasgow Coma Scale (GCS), low blood pressure, or abnormal respiratory rate had the highest probability for sepsis diagnosis.

CONCLUSION

Dispatch categories and elevated temperature identify patients with higher probability of infection, but abnormal GCS, low blood pressure, and abnormal respiratory rate identify patients with infection who have a higher probability of sepsis. These characteristics may be considered by paramedics to identify higher-risk patients prior to arrival at the hospital.

摘要

目的

急救人员通常是感染和败血症患者的第一医疗接触者,通过提高对识别高危患者的临床体征和症状的认识,他们可能更早地识别出这些患者。

方法

对 2015 年 4 月至 2016 年 3 月期间在加拿大艾伯塔省通过急救医疗服务转运的所有成年患者进行了为期 1 年的队列研究,并将这些患者与医院行政数据库进行了关联。主要结局是在急诊科对感染患者的感染或败血症诊断。我们根据急救人员通常可获得的体征和症状,对这些结局发生的可能性进行了估计。

结果

在通过急救医疗服务转运的 131745 例患者中,感染的患病率为 9.7%,败血症为 2.1%。败血症患者的院内死亡率为 28%。大多数(62%)感染患者属于三个调度类别之一(“呼吸问题”、“生病患者”或“机构间转运”),这些类别的患者的感染诊断概率为 17-20%。体温升高的患者感染诊断的可能性最高,但格拉斯哥昏迷量表(GCS)异常、低血压或呼吸频率异常的患者败血症诊断的可能性最高。

结论

调度类别和体温升高可识别出感染可能性较高的患者,但异常的 GCS、低血压和异常的呼吸频率可识别出感染可能性较高的败血症患者。这些特征可被急救人员用于在到达医院之前识别高风险患者。

相似文献

1
Epidemiology and patient predictors of infection and sepsis in the prehospital setting.院前环境中感染和脓毒症的流行病学和患者预测因素。
Intensive Care Med. 2020 Jul;46(7):1394-1403. doi: 10.1007/s00134-020-06093-4. Epub 2020 May 28.
2
[Sepsis detection in emergency medicine : Results of an interprofessional survey on sepsis detection in prehospital emergency medicine and emergency departments].[急诊医学中的脓毒症检测:院前急救医学和急诊科脓毒症检测的跨专业调查结果]
Anaesthesist. 2018 Aug;67(8):584-591. doi: 10.1007/s00101-018-0456-z. Epub 2018 May 25.
3
Classification versus Prediction of Mortality Risk using the SIRS and qSOFA Scores in Patients with Infection Transported by Paramedics.运用 SIRS 和 qSOFA 评分对由急救员转运的感染患者进行死亡率风险的分类与预测。
Prehosp Emerg Care. 2020 Mar-Apr;24(2):282-289. doi: 10.1080/10903127.2019.1624901. Epub 2019 Jun 19.
4
Screening strategies to identify sepsis in the prehospital setting: a validation study.在院前环境中识别脓毒症的筛查策略:一项验证研究。
CMAJ. 2020 Mar 9;192(10):E230-E239. doi: 10.1503/cmaj.190966.
5
Association Between Early Intravenous Fluids Provided by Paramedics and Subsequent In-Hospital Mortality Among Patients With Sepsis.急救人员早期提供的静脉输液与脓毒症患者后续住院死亡率之间的关联。
JAMA Netw Open. 2018 Dec 7;1(8):e185845. doi: 10.1001/jamanetworkopen.2018.5845.
6
Paramedic-Initiated CMS Sepsis Core Measure Bundle Prior to Hospital Arrival: A Stepwise Approach.院前护理人员启动的脓毒症核心测量集:一种逐步方法。
Prehosp Emerg Care. 2017 May-Jun;21(3):291-300. doi: 10.1080/10903127.2016.1254694. Epub 2016 Dec 5.
7
Prehospital Lactate Measurement by Emergency Medical Services in Patients Meeting Sepsis Criteria.符合脓毒症标准患者的院外乳酸测量:由紧急医疗服务机构进行
West J Emerg Med. 2016 Sep;17(5):648-55. doi: 10.5811/westjem.2016.6.30233. Epub 2016 Jul 21.
8
Low sensitivity of qSOFA, SIRS criteria and sepsis definition to identify infected patients at risk of complication in the prehospital setting and at the emergency department triage.qSOFA、SIRS 标准和脓毒症定义对识别院前环境和急诊科分诊中感染风险患者的并发症的敏感性较低。
Scand J Trauma Resusc Emerg Med. 2017 Nov 3;25(1):108. doi: 10.1186/s13049-017-0449-y.
9
The prehospital assessment of patients with a final hospital diagnosis of sepsis: Results of an observational study.对最终医院诊断为脓毒症患者的院前评估:一项观察性研究的结果
Australas Emerg Care. 2019 Sep;22(3):187-192. doi: 10.1016/j.auec.2019.02.002. Epub 2019 Mar 14.
10
An Early Warning Scoring System to Identify Septic Patients in the Prehospital Setting: The PRESEP Score.一种用于在院前环境中识别脓毒症患者的早期预警评分系统:PRESEP评分
Acad Emerg Med. 2015 Jul;22(7):868-71. doi: 10.1111/acem.12707. Epub 2015 Jun 25.

引用本文的文献

1
Construction and efficacy evaluation of a model for early diagnosis of pediatric sepsis based on LASSO-logistic regression.基于LASSO-逻辑回归的小儿脓毒症早期诊断模型的构建与疗效评估
Front Pediatr. 2025 Aug 26;13:1624278. doi: 10.3389/fped.2025.1624278. eCollection 2025.
2
Prehospital antibiotics and intravenous fluids for patients with sepsis: protocol for a 2×2 factorial randomised controlled trial.脓毒症患者的院前抗生素和静脉输液治疗:一项2×2析因随机对照试验方案
BMJ Open. 2025 May 27;15(5):e104257. doi: 10.1136/bmjopen-2025-104257.
3
Interpretive machine learning predicts short-term mortality risk in elderly sepsis patients.
解释性机器学习可预测老年脓毒症患者的短期死亡风险。
Front Physiol. 2025 Mar 26;16:1549138. doi: 10.3389/fphys.2025.1549138. eCollection 2025.
4
The performance of screening tools and use of blood analyses in prehospital identification of sepsis patients and patients suitable for non-conveyance - an observational study.在院前鉴别脓毒症患者和不适合转运患者中,筛选工具的表现和血液分析的使用 - 一项观察性研究。
BMC Emerg Med. 2024 Oct 8;24(1):180. doi: 10.1186/s12873-024-01098-4.
5
Nomogram predictive model for in-hospital mortality risk in elderly ICU patients with urosepsis.老年脓毒症性泌尿系统感染重症监护病房患者院内死亡风险的列线图预测模型
BMC Infect Dis. 2024 Apr 26;24(1):442. doi: 10.1186/s12879-024-09319-8.
6
Sepsis incidence, suspicion, prediction and mortality in emergency medical services: a cohort study related to the current international sepsis guideline.急诊医疗服务中的脓毒症发病率、疑似病例、预测和死亡率:与当前国际脓毒症指南相关的队列研究。
Infection. 2024 Aug;52(4):1325-1335. doi: 10.1007/s15010-024-02181-5. Epub 2024 Feb 19.
7
Pre-hospital Prognostic Factors of 30-Day Survival in Sepsis Patients; a Retrospective Cohort Study.脓毒症患者30天生存的院前预后因素;一项回顾性队列研究。
Arch Acad Emerg Med. 2023 Jul 13;11(1):e48. doi: 10.22037/aaem.v11i1.2029. eCollection 2023.
8
A nomogram to predict prolonged stay of obesity patients with sepsis in ICU: Relevancy for predictive, personalized, preventive, and participatory healthcare strategies.预测 ICU 中肥胖脓毒症患者住院时间延长的列线图:对预测性、个性化、预防性和参与性医疗保健策略的相关性。
Front Public Health. 2022 Aug 11;10:944790. doi: 10.3389/fpubh.2022.944790. eCollection 2022.
9
Ultra-Short-Course Antibiotics for Suspected Pneumonia With Preserved Oxygenation.疑似氧合正常肺炎的超短程抗生素治疗。
Clin Infect Dis. 2023 Feb 8;76(3):e1217-e1223. doi: 10.1093/cid/ciac616.
10
Interpretable Machine Learning for Early Prediction of Prognosis in Sepsis: A Discovery and Validation Study.用于脓毒症预后早期预测的可解释机器学习:一项发现与验证研究。
Infect Dis Ther. 2022 Jun;11(3):1117-1132. doi: 10.1007/s40121-022-00628-6. Epub 2022 Apr 10.