BMJ Open (Apr 2022)

Predictive performance of comorbidity for 30-day and 1-year mortality in patients with bloodstream infection visiting the emergency department: a retrospective cohort study

  • Annelies Verbon,
  • Jelmer Alsma,
  • Hester Lingsma,
  • Anniek Brink,
  • Romy Schuttevaer,
  • William Boogers,
  • Willian van Dijk,
  • Jurriaan de Steenwinkel,
  • Stephanie Schuit

DOI
https://doi.org/10.1136/bmjopen-2021-057196
Journal volume & issue
Vol. 12, no. 4

Abstract

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Objectives To investigate whether the Charlson Comorbidity Index (CCI) predicted short-term and long-term mortality in patients with a bloodstream infection visiting the emergency department (ED) and compare it to the often-validated National Early Warning Score (NEWS).Design A retrospective cohort study.Setting A tertiary hospital in the Netherlands.Participants Adult patients attending the ED with a blood culture-proven infection between 2012 and 2017 were included. We collected the comorbidities from the CCI and the vital signs from the NEWS.Main outcomes Short-term mortality (30-day) and long-term mortality (1 year). We assessed the predictive performance by discrimination, expressed as the area under the curve (AUC).Results We included 1039 patients with a blood culture-proven infection. Mortality was 10.4% within 30 days and 27.8% within 1 year. On average patients had two comorbidities (ranging from 0 to 6). Highly prevalent comorbidities were malignancy (30.2%) and diabetes mellitus (20.5%). The predictive performance of the CCI was highest for 1-year mortality (AUC 0.696 (95%CI) (0.660 to 0.732)) and better compared with the NEWS (AUC (95% CI) 0.594 (0.555 to 0.632)). For prediction of 30-day mortality, the NEWS was superior (AUC (95% CI) 0.706 (0.656 to 0.756)) to the comorbidities of the CCI (AUC (95% CI) 0.568 (0.507 to 0.628)).Conclusions We found that presenting comorbidity (ie, the CCI) is most useful to prognosticate long-term outcome in patients with bloodstream infection in the ED. Short-term mortality is more accurately predicted by deviating vital signs (ie, the NEWS).