Investigating the Impact of Different Suspicion of Infection Criteria on the Accuracy of Quick Sepsis-Related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores*
- 1 November 2017
- journal article
- research article
- Published by Ovid Technologies (Wolters Kluwer Health) in Critical Care Medicine
- Vol. 45 (11), 1805-1812
- https://doi.org/10.1097/ccm.0000000000002648
Abstract
Objective: Studies in sepsis are limited by heterogeneity regarding what constitutes suspicion of infection. We sought to compare potential suspicion criteria using antibiotic and culture order combinations in terms of patient characteristics and outcomes. We further sought to determine the impact of differing criteria on the accuracy of sepsis screening tools and early warning scores. Design: Observational cohort study. Setting: Academic center from November 2008 to January 2016. Patients: Hospitalized patients outside the ICU. Interventions: None. Measurements and Main Results: Six criteria were investigated: 1) any culture, 2) blood culture, 3) any culture plus IV antibiotics, 4) blood culture plus IV antibiotics, 5) any culture plus IV antibiotics for at least 4 of 7 days, and 6) blood culture plus IV antibiotics for at least 4 of 7 days. Accuracy of the quick Sepsis-related Organ Failure Assessment score, Sepsis-related Organ Failure Assessment score, systemic inflammatory response syndrome criteria, the National and Modified Early Warning Score, and the electronic Cardiac Arrest Risk Triage score were calculated for predicting ICU transfer or death within 48 hours of meeting suspicion criteria. A total of 53,849 patients met at least one infection criteria. Mortality increased from 3% for group 1 to 9% for group 6 and percentage meeting Angus sepsis criteria increased from 20% to 40%. Across all criteria, score discrimination was lowest for systemic inflammatory response syndrome (median area under the receiver operating characteristic curve, 0.60) and Sepsis-related Organ Failure Assessment score (median area under the receiver operating characteristic curve, 0.62), intermediate for quick Sepsis-related Organ Failure Assessment (median area under the receiver operating characteristic curve, 0.65) and Modified Early Warning Score (median area under the receiver operating characteristic curve 0.67), and highest for National Early Warning Score (median area under the receiver operating characteristic curve 0.71) and electronic Cardiac Arrest Risk Triage (median area under the receiver operating characteristic curve 0.73). Conclusions: The choice of criteria to define a potentially infected population significantly impacts prevalence of mortality but has little impact on accuracy. Systemic inflammatory response syndrome was the least predictive and electronic Cardiac Arrest Risk Triage the most predictive regardless of how infection was defined.Keywords
This publication has 21 references indexed in Scilit:
- Assessment of Clinical Criteria for SepsisJAMA, 2016
- Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the WardsCritical Care Medicine, 2016
- Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward PatientsAmerican Journal of Respiratory and Critical Care Medicine, 2015
- Reduction in Time to First Action as a Result of Electronic Alerts for Early Sepsis RecognitionCritical Care Nursing Quarterly, 2015
- Development, implementation, and impact of an automated early warning and response system for sepsisJournal of Hospital Medicine, 2014
- Multicenter Development and Validation of a Risk Stratification Tool for Ward PatientsAmerican Journal of Respiratory and Critical Care Medicine, 2014
- Hospital Deaths in Patients With Sepsis From 2 Independent CohortsJAMA, 2014
- Identifying Patients With Severe Sepsis Using Administrative ClaimsMedical Care, 2014
- Severe Sepsis Cohorts Derived From Claims-Based Strategies Appear to be Biased Toward a More Severely Ill Patient Population*Critical Care Medicine, 2013
- Early prediction of septic shock in hospitalized patientsJournal of Hospital Medicine, 2010