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Factors associated with acquisition of glycopeptide-resistant enterococci during a single-strain outbreak.


ABSTRACT: The aim of our study was to describe and to investigate the factors associated with glycopeptide-resistant enterococci (GRE) acquisition during a single-strain outbreak which occurred in several wards of hospital from September 2013 to January 2014. We designed a case-control study. Analyses were performed using Bayesian methods. Univariate logistic regressions with informative priors from published studies were conducted. A multivariate model was build including variables with a probability of odd-ratio exceeding one (Pr) >85% or <15%. Thirteen cases and 52 controls were recruited. The description of this outbreak highlighted the importance to quickly detect patients at risk of GRE carriage in order to implement the isolation measures and to transfer to dedicated department if they are effectively carriers. Following multivariate analysis, antibiotics during hospitalisation (Pr = 0.968), number of hospitalisation days in the year (Pr = 0.964), antacids intake (Pr = 0.878) (with a risk increase), immunosuppression (Pr = 0.026) and isolation measures (Pr = 0.003) (both with protective effect) were associated with GRE acquisition. The use of Bayesian statistics was useful because of our study's small population size and prior information availability.

SUBMITTER: Deboscker S 

PROVIDER: S-EPMC6518758 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Factors associated with acquisition of glycopeptide-resistant enterococci during a single-strain outbreak.

Deboscker S S   Schneider P P   Séverac F F   Ménard C C   Gaudart J J   Lavigne T T   Meyer N N  

Epidemiology and infection 20190101


The aim of our study was to describe and to investigate the factors associated with glycopeptide-resistant enterococci (GRE) acquisition during a single-strain outbreak which occurred in several wards of hospital from September 2013 to January 2014. We designed a case-control study. Analyses were performed using Bayesian methods. Univariate logistic regressions with informative priors from published studies were conducted. A multivariate model was build including variables with a probability of  ...[more]

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