↓ Skip to main content

Screening swabs surpass traditional risk factors as predictors of MRSA bacteremia

Overview of attention for article published in BMC Infectious Diseases, June 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
18 tweeters

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
22 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Screening swabs surpass traditional risk factors as predictors of MRSA bacteremia
Published in
BMC Infectious Diseases, June 2018
DOI 10.1186/s12879-018-3182-x
Pubmed ID
Authors

Guillaume Butler-Laporte, Matthew P. Cheng, Emily G. McDonald, Todd C. Lee

Abstract

Consideration to add empiric MRSA therapy with vancomycin is a common clinical dilemma. However, vancomycin overuse has important adverse events. MRSA colonization screening is commonly performed for infection control. We hypothesized that in cases of S. aureus bacteremia, a score based on patient level factors and MRSA colonization could predict the risk of MRSA infection and inform the need for empiric coverage. Using modern machine learning statistical methods (LASSO regression and random forests), we designed a predictive score for MRSA infection based on patient level characteristics, and MRSA colonization as measured by screening done 30 days before infection (30-Day criteria), or at any time before infection (Ever-Positive criteria). Patient factors (age, sex, number of previous admissions, and other medical comorbidities) were obtained through our electronic records. With random forests, MRSA colonization largely surpassed all other factors in terms of accuracy and discriminatory power. Using LASSO regression, MRSA colonization was the only factor with MRSA infection predictive power with odds ratio of 10.3 (min: 5.99, max: 16.1) and 8.14 (min: 6.01, max: 14.8) for the 30-Day and Ever-Positive criteria, respectively. Further, patient comorbidities were not adequate predictors of MRSA colonization. In an era of community acquired MRSA, colonization status appears to be the only independent and reliable predictor of MRSA infection in cases of S. aureus bacteremia. A clinical approach based on a patient's known MRSA colonization status and on local susceptibility patterns may be appropriate.

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Other 5 23%
Student > Master 3 14%
Researcher 3 14%
Student > Doctoral Student 2 9%
Student > Postgraduate 2 9%
Other 2 9%
Unknown 5 23%
Readers by discipline Count As %
Medicine and Dentistry 7 32%
Pharmacology, Toxicology and Pharmaceutical Science 4 18%
Biochemistry, Genetics and Molecular Biology 2 9%
Nursing and Health Professions 1 5%
Social Sciences 1 5%
Other 1 5%
Unknown 6 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 22 November 2022.
All research outputs
#1,389,123
of 22,559,910 outputs
Outputs from BMC Infectious Diseases
#317
of 7,605 outputs
Outputs of similar age
#30,731
of 301,344 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
Altmetric has tracked 22,559,910 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,605 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one has done particularly well, scoring higher than 95% of its peers.
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 301,344 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them