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The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital

Overview of attention for article published in BMC Infectious Diseases, July 2014
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Title
The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital
Published in
BMC Infectious Diseases, July 2014
DOI 10.1186/1471-2334-14-375
Pubmed ID
Authors

Meredith C Faires, David L Pearl, William A Ciccotelli, Olaf Berke, Richard J Reid-Smith, J Scott Weese

Abstract

In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in under- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are generally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant differences in the rate of MRSA cases using regression models.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 2%
Unknown 42 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 16%
Student > Master 7 16%
Student > Ph. D. Student 6 14%
Student > Bachelor 5 12%
Lecturer 3 7%
Other 7 16%
Unknown 8 19%
Readers by discipline Count As %
Medicine and Dentistry 11 26%
Agricultural and Biological Sciences 6 14%
Social Sciences 3 7%
Immunology and Microbiology 2 5%
Nursing and Health Professions 2 5%
Other 8 19%
Unknown 11 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 July 2014.
All research outputs
#20,233,066
of 22,758,963 outputs
Outputs from BMC Infectious Diseases
#6,454
of 7,664 outputs
Outputs of similar age
#190,357
of 225,827 outputs
Outputs of similar age from BMC Infectious Diseases
#134
of 147 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,664 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one is in the 1st percentile – i.e., 1% 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 225,827 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.