Carolina Hincapié-Osorno, Raymond J van Wijk, Douwe F Postma, Jacqueline Koeze, Jan C Ter Maaten, Fabian Jaimes, Hjalmar R Bouma
{"title":"针对急诊科不同感染灶的 MEWS、NEWS、NEWS-2 和 qSOFA 验证,acutelines 队列。","authors":"Carolina Hincapié-Osorno, Raymond J van Wijk, Douwe F Postma, Jacqueline Koeze, Jan C Ter Maaten, Fabian Jaimes, Hjalmar R Bouma","doi":"10.1007/s10096-024-04961-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Sepsis is a leading cause of morbidity and mortality globally. The lack of specific prognostic markers necessitates tools for early risk identification in patients with suspected infections in emergency department (ED). This study evaluates the prognostic accuracy of various Early Warning Scores (EWS)-MEWS, NEWS, NEWS-2, and qSOFA-for in-hospital mortality, 30-day mortality, and ICU admission, considering the site of infection.</p><p><strong>Methods: </strong>A retrospective analysis was conducted using data from the Acutelines cohort, which included data collected from patients admitted to the University Medical Centre Groningen ED between September 2020 and July 2023. Patients were included if they had an ICD-10 code for infection. EWS were calculated using clinical data within 8 h post-admission. Predictive performance was assessed using AUC-ROC, calibration by the Hosmer-Lemeshow test and calibration curves, and operative characteristics like sensitivity and specificity.</p><p><strong>Results: </strong>A total of 1661 patients were analyzed, with infections distributed as follows: lower respiratory tract (32.9%), urinary tract (30.7%), abdominal (12.5%), skin and soft tissue (9.5%), and others (8.2%). The overall in-hospital mortality was 6.7%, and ICU admission was 7.1%. The highest AUC-ROC for in-hospital mortality prediction was observed with NEWS and NEWS-2 in abdominal infections (0.86), while the lowest was for qSOFA in skin and soft tissue infections (0.57). Predictive performance varied by infection site.</p><p><strong>Conclusions: </strong>The study highlights the variability in EWS performance based on infection site, emphasizing the need to consider the source of infection in EWS development for sepsis prognosis. Tailored or hybrid models may enhance predictive accuracy, balancing simplicity and specificity.</p>","PeriodicalId":11782,"journal":{"name":"European Journal of Clinical Microbiology & Infectious Diseases","volume":" ","pages":"2441-2452"},"PeriodicalIF":3.7000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of MEWS, NEWS, NEWS-2 and qSOFA for different infection foci at the emergency department, the acutelines cohort.\",\"authors\":\"Carolina Hincapié-Osorno, Raymond J van Wijk, Douwe F Postma, Jacqueline Koeze, Jan C Ter Maaten, Fabian Jaimes, Hjalmar R Bouma\",\"doi\":\"10.1007/s10096-024-04961-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Sepsis is a leading cause of morbidity and mortality globally. The lack of specific prognostic markers necessitates tools for early risk identification in patients with suspected infections in emergency department (ED). This study evaluates the prognostic accuracy of various Early Warning Scores (EWS)-MEWS, NEWS, NEWS-2, and qSOFA-for in-hospital mortality, 30-day mortality, and ICU admission, considering the site of infection.</p><p><strong>Methods: </strong>A retrospective analysis was conducted using data from the Acutelines cohort, which included data collected from patients admitted to the University Medical Centre Groningen ED between September 2020 and July 2023. Patients were included if they had an ICD-10 code for infection. EWS were calculated using clinical data within 8 h post-admission. Predictive performance was assessed using AUC-ROC, calibration by the Hosmer-Lemeshow test and calibration curves, and operative characteristics like sensitivity and specificity.</p><p><strong>Results: </strong>A total of 1661 patients were analyzed, with infections distributed as follows: lower respiratory tract (32.9%), urinary tract (30.7%), abdominal (12.5%), skin and soft tissue (9.5%), and others (8.2%). The overall in-hospital mortality was 6.7%, and ICU admission was 7.1%. The highest AUC-ROC for in-hospital mortality prediction was observed with NEWS and NEWS-2 in abdominal infections (0.86), while the lowest was for qSOFA in skin and soft tissue infections (0.57). Predictive performance varied by infection site.</p><p><strong>Conclusions: </strong>The study highlights the variability in EWS performance based on infection site, emphasizing the need to consider the source of infection in EWS development for sepsis prognosis. Tailored or hybrid models may enhance predictive accuracy, balancing simplicity and specificity.</p>\",\"PeriodicalId\":11782,\"journal\":{\"name\":\"European Journal of Clinical Microbiology & Infectious Diseases\",\"volume\":\" \",\"pages\":\"2441-2452\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Clinical Microbiology & Infectious Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10096-024-04961-1\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/16 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Clinical Microbiology & Infectious Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10096-024-04961-1","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/16 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Validation of MEWS, NEWS, NEWS-2 and qSOFA for different infection foci at the emergency department, the acutelines cohort.
Purpose: Sepsis is a leading cause of morbidity and mortality globally. The lack of specific prognostic markers necessitates tools for early risk identification in patients with suspected infections in emergency department (ED). This study evaluates the prognostic accuracy of various Early Warning Scores (EWS)-MEWS, NEWS, NEWS-2, and qSOFA-for in-hospital mortality, 30-day mortality, and ICU admission, considering the site of infection.
Methods: A retrospective analysis was conducted using data from the Acutelines cohort, which included data collected from patients admitted to the University Medical Centre Groningen ED between September 2020 and July 2023. Patients were included if they had an ICD-10 code for infection. EWS were calculated using clinical data within 8 h post-admission. Predictive performance was assessed using AUC-ROC, calibration by the Hosmer-Lemeshow test and calibration curves, and operative characteristics like sensitivity and specificity.
Results: A total of 1661 patients were analyzed, with infections distributed as follows: lower respiratory tract (32.9%), urinary tract (30.7%), abdominal (12.5%), skin and soft tissue (9.5%), and others (8.2%). The overall in-hospital mortality was 6.7%, and ICU admission was 7.1%. The highest AUC-ROC for in-hospital mortality prediction was observed with NEWS and NEWS-2 in abdominal infections (0.86), while the lowest was for qSOFA in skin and soft tissue infections (0.57). Predictive performance varied by infection site.
Conclusions: The study highlights the variability in EWS performance based on infection site, emphasizing the need to consider the source of infection in EWS development for sepsis prognosis. Tailored or hybrid models may enhance predictive accuracy, balancing simplicity and specificity.
期刊介绍:
EJCMID is an interdisciplinary journal devoted to the publication of communications on infectious diseases of bacterial, viral and parasitic origin.