4.7 Article

A Prognostic Model of Persistent Bacteremia and Mortality in Complicated Staphylococcus aureus Bloodstream Infection

期刊

CLINICAL INFECTIOUS DISEASES
卷 68, 期 9, 页码 1502-1511

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/ciy739

关键词

Staphylococcus aureus; bacteremia; endocarditis; prognostic biomarkers

资金

  1. Genentech, Inc.
  2. National Center for Advancing Translational Sciences of the National Institutes of Health [1KL2TR002554]

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Background. Staphylococcus aureus is a leading cause of bacteremia, yet there remains a significant knowledge gap in the identification of relevant biomarkers that predict clinical outcomes. Heterogeneity in the host response to invasive S. aureus infection suggests that specific biomarker signatures could be utilized to differentiate patients prone to severe disease, thereby facilitating earlier implementation of more aggressive therapies. Methods. To further elucidate the inflammatory correlates of poor clinical outcomes in patients with S. aureus bacteremia, we evaluated the association between a panel of blood proteins at initial presentation of bacteremia and disease severity outcomes using 2 cohorts of patients with S. aureus bacteremia (n = 32 and n = 124). Results. We identified 13 candidate proteins that were correlated with mortality and persistent bacteremia. Prognostic modeling identified interleukin (IL)-8 and CCL2 as the strongest individual predictors of mortality, with the combination of these biomarkers classifying fatal outcome with 89% sensitivity and 77% specificity (P < .0001). Baseline IL-17A levels were elevated in patients with persistent bacteremia (P < .0001), endovascular (P = .026) and metastatic tissue infections (P = .012). Conclusions. These results demonstrate the potential utility of selected biomarkers to distinguish patients with the highest risk for treatment failure and bacteremia-related complications, providing a valuable tool for clinicians in the management of S. aureus bacteremia. Additionally, these biomarkers could identify patients with the greatest potential to benefit from novel therapies in clinical trials.

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