Background: Measuring sepsis incidence and associated mortality at scale using administrative data is hampered by variation in diagnostic coding. This study aimed first to compare how well bedside severity scores predict 30-day mortality in hospitalised patients with infection, then to assess the ability of combinations of administrative data items to identify patients with sepsis.
Methods: This retrospective case note review examined 958 adult hospital admissions between October 2015 and March 2016. Admissions with blood culture sampling were matched 1:1 to admissions without a blood culture. Case note review data were linked to discharge coding and mortality. For patients with infection the performance characteristics of Sequential Organ Failure Assessment (SOFA), National Early Warning System (NEWS), quick SOFA (qSOFA), and Systemic Inflammatory Response Syndrome (SIRS) were calculated for predicting 30-day mortality. Next, the performance characteristics of administrative data (blood cultures and discharge codes) for identifying patients with sepsis, defined as SOFA ≥2 because of infection, were calculated.
Results: Infection was documented in 630 (65.8%) admissions and 347 (55.1%) patients with infection had sepsis. NEWS (Area Under the Receiver Operating Characteristic, AUROC 0.78 95%CI 0.72-0.83) and SOFA (AUROC 0.77, 95%CI 0.72-0.83), performed similarly well for prediction of 30-day mortality. Having an infection and/or sepsis International Classification of Diseases, Tenth Revision (ICD-10) code (AUROC 0.68, 95%CI 0.64-0.71) performed as well in identifying patients with sepsis as having at least one of: an infection code; sepsis code, or; blood culture (AUROC 0.68, 95%CI 0.65-0.71), Sepsis codes (AUROC 0.53, 95%CI 0.49-0.57) and positive blood cultures (AUROC 0.52, 95%CI 0.49-0.56) performed least well.
Conclusions: SOFA and NEWS best predicted 30-day mortality in patients with infection. Sepsis ICD-10 codes lack sensitivity. For health systems without suitable electronic health records, blood culture sampling has potential utility as a clinical component of a proxy marker for sepsis surveillance.
Copyright: © 2023 Bateson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.