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Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?

Overview of attention for article published in PLOS ONE, December 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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7 X users

Citations

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8 Dimensions

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58 Mendeley
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Title
Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?
Published in
PLOS ONE, December 2015
DOI 10.1371/journal.pone.0145088
Pubmed ID
Authors

Élise Fortin, Robert W. Platt, Patricia S. Fontela, David L. Buckeridge, Caroline Quach

Abstract

The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs), this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy. Retrospective cohort study including all patients admitted to three neonatal (NICU), two pediatric (PICU) and four adult ICUs between April 2006 and March 2010. Ten different resistance / antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE) in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests. Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006). A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 17%
Student > Postgraduate 8 14%
Student > Bachelor 7 12%
Researcher 7 12%
Student > Ph. D. Student 4 7%
Other 8 14%
Unknown 14 24%
Readers by discipline Count As %
Medicine and Dentistry 20 34%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Agricultural and Biological Sciences 4 7%
Nursing and Health Professions 3 5%
Business, Management and Accounting 2 3%
Other 8 14%
Unknown 17 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 August 2016.
All research outputs
#7,469,754
of 22,836,570 outputs
Outputs from PLOS ONE
#89,044
of 194,874 outputs
Outputs of similar age
#122,720
of 392,255 outputs
Outputs of similar age from PLOS ONE
#1,900
of 4,917 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,874 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 49th percentile – i.e., 49% 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 392,255 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 4,917 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.