Molecular epidemiology of Pseudomonas aeruginosa isolated from infected ICU patients: a French multicenter 2012-2013

Céline Slekovec1,2, Jérôme Robert3, Nathalie van der Mee-Marquet4

  • 1Hygiène Hospitalière, Centre Hospitalier Régional Universitaire, Besançon, France.

Insights

Pseudomonas aeruginosa infections in French ICUs show high diversity, but seven epidemic high-risk clones dominate, especially among multidrug-resistant isolates. These clones spread within hospitals, sometimes acquiring resistance over time.

Area of Science:

  • Medical Microbiology
  • Epidemiology
  • Infectious Diseases

Background:

  • Pseudomonas aeruginosa exhibits a complex population structure, with emerging evidence of epidemic high-risk clones.
  • Understanding the molecular epidemiology of P. aeruginosa is crucial for controlling hospital-acquired infections.

Purpose of the Study:

  • To investigate the molecular epidemiology of P. aeruginosa causing infections in French intensive care units (ICUs).
  • To identify dominant clones and their association with antimicrobial resistance patterns.

Main Methods:

  • Antimicrobial susceptibility testing and genotyping (multilocus sequence typing and pulsed-field gel electrophoresis) were performed on P. aeruginosa isolates.
  • Phenotypic and sequencing methods identified extended-spectrum beta-lactamases.
  • Isolates from bacteremia and pulmonary infections in ICUs were analyzed.

Main Results:

  • 104 P. aeruginosa isolates comprised 46 sequence types (STs), with 7 epidemic high-risk (EHR) clones being over-represented.
  • Multidrug-resistant (MDR) isolates were predominantly associated with these EHR clones.
  • Intra-hospital cross-transmission of EHR clones was observed, with some acquiring MDR over time.

Conclusions:

  • French ICUs experience P. aeruginosa infections with significant clonal diversity, alongside the prevalence of specific EHR clones.
  • EHR clones are key drivers of MDR P. aeruginosa infections in ICUs, though resistance is not an inherent trait.
  • Molecular surveillance is essential for tracking P. aeruginosa epidemiology and guiding infection control strategies.

Related Concept Videos

Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
954
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
783
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.3K
Introduction to Epidemiology01:26

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.8K
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
938