TY - JOUR
T1 - Validation of MEWS, NEWS, NEWS-2 and qSOFA for different infection foci at the emergency department, the acutelines cohort
AU - Hincapié-Osorno, Carolina
AU - van Wijk, Raymond J
AU - Postma, Douwe F
AU - Koeze, Jacqueline
AU - Ter Maaten, Jan C
AU - Jaimes, Fabian
AU - Bouma, Hjalmar R
N1 - © 2024. The Author(s).
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
U2 - 10.1007/s10096-024-04961-1
DO - 10.1007/s10096-024-04961-1
M3 - Article
C2 - 39414696
SN - 0934-9723
VL - 43
SP - 2441
EP - 2452
JO - European Journal of Clinical Microbiology & Infectious Diseases
JF - European Journal of Clinical Microbiology & Infectious Diseases
ER -