Abstract
Enterobacteriaceae is a leading pathogen of community-onset bacteremia. This study aims to establish a predictive scoring algorithm to identify adults with community-onset Enterobacteriaceae bacteremia who are at risk for abscesses. Of the total 1262 adults, 152 (12.0%) with abscess occurrence were noted. The 6 risk factors significantly associated with abscess occurrence-liver cirrhosis, diabetes mellitus, thrombocytopenia and high C-reactive protein (>100 mg/L) at bacteremic onset, delayed defervescence, and bacteremia-causing Klebsiella pneumoniae-were each assigned +1 point to form the scoring algorithm. In contrast, the elderly, fatal comorbidity (McCabe classification), and bacteremia-causing Escherichia coli were each assigned -1 point, owing to their negative associations with abscess occurrence. Using the proposed scoring algorithm, a cut-off value of +1 yielded a high sensitivity (85.5%) and an acceptable specificity (60.4%). Although the proposed predictive model needs further validation, this simple scoring algorithm may be useful for the early identification of abscesses by clinicians.
| Original language | English |
|---|---|
| Pages (from-to) | 74-79 |
| Number of pages | 6 |
| Journal | Diagnostic Microbiology and Infectious Disease |
| Volume | 84 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2016 Jan 1 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Microbiology (medical)
- Infectious Diseases
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