| Literature DB >> 27863948 |
Young Kyung Yoon1, Hyun Ah Kim2, Seong Yeol Ryu2, Eun Jung Lee3, Mi Suk Lee4, Jieun Kim5, Seong Yeon Park6, Kyung Sook Yang7, Shin Woo Kim8.
Abstract
This study aimed to construct a prediction algorithm, which is readily applicable in the clinical setting, to determine the mortality rate for patients with P. aeruginosa bacteremia. A multicenter observational cohort study was performed retrospectively in seven university-affiliated hospitals in Korea from March 2012 to February 2015. In total, 264 adult patients with monomicrobial P. aeruginosa bacteremia were included in the analyses. Among the predictors independently associated with 30-day mortality in the Cox regression model, Pitt bacteremia score >2 and high-risk source of bacteremia were identified as critical nodes in the tree-structured survival analysis. Particularly, the empirical combination therapy was not associated with any survival benefit in the Cox regression model compared to the empirical monotherapy. This study suggests that determining the infection source and evaluating the clinical severity are critical to predict the clinical outcome in patients with P. aeruginosa bacteremia.Entities:
Keywords: Bacteremia; Mortality; Pseudomonas aeruginosa
Mesh:
Year: 2016 PMID: 27863948 DOI: 10.1016/j.diagmicrobio.2016.10.008
Source DB: PubMed Journal: Diagn Microbiol Infect Dis ISSN: 0732-8893 Impact factor: 2.803