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Challenges in interpretation of WGS and epidemiological data to investigate nosocomial transmission of vancomycin-resistant Enterococcus faecium in an endemic region: incorporation of patient movement network and admission screening
OBJECTIVES: VRE are listed, by the WHO, among the leading resistant pathogens causing greatest public concern; hence the spread and transmission of VRE, especially in hospitalized patients, need to be monitored. Despite the advancements in typing methods since the implementation of WGS for outbreak...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303815/ https://www.ncbi.nlm.nih.gov/pubmed/32413123 http://dx.doi.org/10.1093/jac/dkaa122 |
Sumario: | OBJECTIVES: VRE are listed, by the WHO, among the leading resistant pathogens causing greatest public concern; hence the spread and transmission of VRE, especially in hospitalized patients, need to be monitored. Despite the advancements in typing methods since the implementation of WGS for outbreak investigations, data interpretation, especially for vancomycin-resistant Enterococcus faecium (VREfm) in an endemic setting, remains challenging. In this study we explored the potential added benefit of incorporating patient movement data and admission screening to accurately estimate the magnitude of an outbreak. METHODS: We sequenced 73 VREfm isolates from patients with bacteraemia (n = 43) and rectal colonization (n = 30/32). Genetic relatedness was determined by SNP distance (≤10) between isolates. Patient movements were visualized in a movement network, along with contact intensity and rectal colonization status prior to infection onset. RESULTS: ST117, ST80 and ST203 were the predominant STs in our study population. Forty-four percent (18/41) of VREfm bacteraemia cases were of endogenous origin. SNP analysis of infection and colonization isolates revealed nine clonal groups. Eighty-six percent (37/43) of the patients were visualized in a transmission network due to spatiotemporal overlap. Nineteen out of 43 (44%) belonged to five transmission clusters. Incorporation of prior colonization status revealed that transmission was very likely in only 63% (12/19) of patients in these transmission clusters. DISCUSSION: Although interpretation of WGS data is challenging, incorporation of patient movement data and colonization status by admission screening of high-risk patients may provide additional resolution when interpreting the magnitude of an outbreak in an endemic setting. |
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