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Epidemiological characterization of a nosocomial outbreak of extended spectrum β‐lactamase Escherichia coli ST‐131 confirms the clinical value of core genome multilocus sequence typing

Overview of attention for article published in APMIS, September 2017
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Title
Epidemiological characterization of a nosocomial outbreak of extended spectrum β‐lactamase Escherichia coli ST‐131 confirms the clinical value of core genome multilocus sequence typing
Published in
APMIS, September 2017
DOI 10.1111/apm.12753
Pubmed ID
Authors

Hanna Woksepp, Anna Ryberg, Linda Berglind, Thomas Schön, Jan Söderman

Abstract

Enhanced precision of epidemiological typing in clinically suspected nosocomial outbreaks is crucial. Our aim was to investigate whether single nucleotide polymorphism (SNP) analysis and core genome (cg) multilocus sequence typing (MLST) of whole genome sequencing (WGS) data would more reliably identify a nosocomial outbreak, compared to earlier molecular typing methods. Sixteen isolates from a nosocomial outbreak of ESBL E. coli ST-131 in southeastern Sweden and three control strains were subjected to WGS. Sequences were explored by SNP analysis and cgMLST. cgMLST clearly differentiated between the outbreak isolates and the control isolates (>1400 differences). All clinically identified outbreak isolates showed close clustering (≥2 allele differences), except for two isolates (>50 allele differences). These data confirmed that the isolates with >50 differing genes did not belong to the nosocomial outbreak. The number of SNPs within the outbreak was ≤7, whereas the two discrepant isolates had >700 SNPs. Two of the ESBL E. coli ST-131 isolates did not belong to the clinically identified outbreak. Our results illustrate the power of WGS in terms of resolution, which may avoid overestimation of patients belonging to outbreaks as judged from epidemiological data and previously employed molecular methods with lower discriminatory ability.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 5 21%
Student > Ph. D. Student 4 17%
Student > Master 4 17%
Researcher 2 8%
Student > Bachelor 2 8%
Other 2 8%
Unknown 5 21%
Readers by discipline Count As %
Medicine and Dentistry 6 25%
Biochemistry, Genetics and Molecular Biology 5 21%
Immunology and Microbiology 4 17%
Unspecified 1 4%
Environmental Science 1 4%
Other 1 4%
Unknown 6 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 October 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from APMIS
#1,612
of 1,741 outputs
Outputs of similar age
#289,102
of 328,838 outputs
Outputs of similar age from APMIS
#8
of 9 outputs
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