Objectives: The aim of this study was to identify clonally-related carbapenemase-producing Klebsiella pneumoniae complex members that could be involved in outbreaks among hospitalized patients in Denmark, and to identify possible epidemiological links.
Methods: From January 2014 to June 2018, 103 isolates belonging to the K. pneumoniae complex were collected from 102 patients. From the whole-genome sequencing (WGS) data, presence of genes encoding carbapenemase and multilocal sequence typing (MLST) data were extracted. Core genome MLST (cgMLST) cluster analysis was performed. Using data from the Danish National Patient Registry (DNPR) and reported travel history, presumptive outbreaks were investigated for possible epidemiological links.
Results: The most common detected carbapenemase gene was bla, followed by bla The 103 K. pneumoniae complex isolates belonged to 47 sequence types (STs) and cgMLST subdivided the isolates into 80 different complex types. cgMLST identified 13 clusters with 2-4 isolates per cluster. For five of the 13 clusters, a direct link (the patients stayed at the same ward on the same day) could be detected between at least some of the patients. In two clusters, the patients resided simultaneously at the same hospital, but not the same ward. A possible link (same ward within 1-13 days) was detected for the patients in one cluster. For five clusters detected by cgMLST, no epidemiological link could be detected using data from DNPR.
Conclusion: In this study, cgMLST combined with patient hospital admission data and travel information was found to be a reliable and detailed approach to detect possible clonal transmission of carbapenemase-producing K. pneumoniae complex members.
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http://dx.doi.org/10.1016/j.ijantimicag.2020.105931 | DOI Listing |
Sci Rep
December 2024
Department of Computer Sciences and Industries, Universidad Católica del Maule, Talca, Chile.
Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating advanced predictive models to support clinical decision-making. In this study, we explore multi-label classification as a novel approach to predict antibiotic resistance across four clinically relevant bacteria: E. coli, S.
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December 2024
Centre for Infectious Diseases Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.
Understanding the impact of different types of social interactions is key to improving epidemic models. Here, we use extensive registry data-including PCR test results and population-level networks-to investigate the impact of school, family, and other social contacts on SARS-CoV-2 transmission in the Netherlands (June 2020-October 2021). We isolate and compare different contexts of potential SARS-CoV-2 transmission by matching pairs of students based on their attendance at the same or different primary school (in 2020) and secondary school (in 2021) and their geographic proximity.
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December 2024
Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Background: Vancomycin, an antibiotic with activity against methicillin-resistant Staphylococcus aureus (MRSA), is frequently included in empiric treatment for community-acquired pneumonia (CAP) despite the fact that MRSA is rarely implicated in CAP. Conducting polymerase chain reaction (PCR) testing on nasal swabs to identify the presence of MRSA colonization has been proposed as an antimicrobial stewardship intervention to reduce the use of vancomycin. Observational studies have shown reductions in vancomycin use after implementation of MRSA colonization testing, and this approach has been adopted by CAP guidelines.
View Article and Find Full Text PDFBackground: Understanding site-related factors that influence enrolment within multicenter randomized controlled trials (RCT) may help reduce trial delays and cost over-runs and prevent early trial discontinuation. In this analysis of PROSPECT (Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial), we describe patient enrolment patterns and examine factors influencing site-based monthly enrolment.
Design: Retrospective analysis of a multicenter RCT.
Sci Rep
December 2024
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, 600127, Chennai, India.
In the current scenario, decision-making models are essential for analyzing real-world problems. To address the dynamic nature of these problems, fuzzy decision-making models have been proposed by various researchers. However, an advanced technique is needed to assess uncertainty in real-time complex situations.
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