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Interobserver Agreement for Classifying Infections in Emergency Department Patients Using Modified Centers for
Oren Turgman1, Evelien Reijnders1, Sebastiaan C M Joosten1
1Centre for Infection and Molecular Medicine, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Amsterdam, The Netherlands.
Background:
To develop and evaluate a standardized emergency department (ED) adapted framework based on Centers for Disease Control (CDC) surveillance definitions and modified SOFA assessment for reproducible infection and sepsis classification in patients with suspected infection on the ED.
Methods:
As part of the prospective cohort study BIOSEP, adults presenting to the ED with suspected infection and a Modified Early Warning Score ≥2 were consecutively enrolled between 2022 and 2026 at 4 Dutch hospitals. All enrolled patients in this study were retrospectively adjudicated through post hoc review of their electronic health records. Each case was independently assessed by 2 blinded physicians for plausibility of infection, infection diagnosis, causative pathogen, and sepsis occurrence. Disagreements were resolved by a third blinded reviewer. Interobserver agreement was quantified using Cohen's kappa and Gwet's agreement coefficients (gAC).
Results:
In total, 1062 ED patients were included with 1145 infection episodes. Interobserver agreement for infection diagnosis was 88.9%, and agreement statistics were classified as very good with Cohen's κ of 0.87 (95% CI 0.85-0.89) and a gAC1 of 0.89 (0.87-0.91). Agreement for causative pathogens was 90.1% (κ 0.89 [0.87-0.92]; gAC1 0.97 [0.95-0.98]), and for sepsis occurrence 93.4% (κ 0.80 [0.76-0.85]; gAC1 0.92 [0.90-0.94]). Agreement for plausibility of infection was also high (87.9%; weighted κ 0.87 [0.85-0.89]; gAC2 0.92 [0.90-0.93]).
Conclusions:
Our ED-adapted adjudication framework based on CDC surveillance definitions yields high interobserver agreement for infection and sepsis classification across a heterogeneous ED population, supporting its use in large-scale observational research.
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