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Regional variations in fluoroquinolone non-susceptibility among Escherichia coli bloodstream infections within the Veterans Healthcare Administration

Overview of attention for article published in Antimicrobial Resistance & Infection Control, October 2016
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Title
Regional variations in fluoroquinolone non-susceptibility among Escherichia coli bloodstream infections within the Veterans Healthcare Administration
Published in
Antimicrobial Resistance & Infection Control, October 2016
DOI 10.1186/s13756-016-0135-2
Pubmed ID
Authors

Daniel J. Livorsi, Michihiko Goto, Margaret Carrel, Makoto M. Jones, Jennifer McDanel, Rajeshwari Nair, Bruce Alexander, Brice Beck, Kelly K. Richardson, Eli N. Perencevich

Abstract

We sought to define regional variations in fluoroquinolone non-susceptibility (FQ-NS) among bloodstream isolates of Escherichia coli across the Veterans Health Administration (VHA) in the United States. We analyzed a retrospective cohort of patients managed at 136 VHA hospitals who had a blood culture positive for E.coli between 2003 and 2013. Hospitals were classified based on US Census Divisions, and regional variations in FQ-NS were analyzed. Twenty-four thousand five hundred twenty-three unique E.coli bloodstream infections (BSIs) were identified between 2003 and 2013. 53.9 % of these were community-acquired, 30.7 % were healthcare-associated, and 15.4 % were hospital-onset BSIs. The proportion of E.coli BSIs with FQ-NS significantly varied across US Census Divisions (p < 0.001). During 2003-2013, the proportion of E.coli BSIs with FQ-NS was highest in the West South-Central Division (32.7 %) and lowest in the Mountain Division (20.0 %). Multivariable analysis showed that there were universal secular trends towards higher FQ-NS rates (p < 0.001) with significant variability of slopes across US Census Divisions (p < 0.001). There has been a universal increase in FQ-NS among E.coli BSIs within VHA, but the rate of increase has significantly varied across Census Divisions. The reasons for this variability are unclear. These findings reinforce the importance of using local data to develop and update local antibiograms and antibiotic-prescribing guidelines.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Other 6 35%
Student > Bachelor 3 18%
Student > Ph. D. Student 2 12%
Researcher 2 12%
Professor 1 6%
Other 2 12%
Unknown 1 6%
Readers by discipline Count As %
Medicine and Dentistry 6 35%
Environmental Science 2 12%
Pharmacology, Toxicology and Pharmaceutical Science 2 12%
Mathematics 2 12%
Nursing and Health Professions 1 6%
Other 1 6%
Unknown 3 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 November 2016.
All research outputs
#16,626,847
of 25,250,629 outputs
Outputs from Antimicrobial Resistance & Infection Control
#1,083
of 1,445 outputs
Outputs of similar age
#198,282
of 323,557 outputs
Outputs of similar age from Antimicrobial Resistance & Infection Control
#20
of 22 outputs
Altmetric has tracked 25,250,629 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,445 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 323,557 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.