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Use of simple clinical and laboratory predictors to differentiate influenza from dengue and other febrile illnesses in the emergency room

Overview of attention for article published in BMC Infectious Diseases, November 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
59 Mendeley
Title
Use of simple clinical and laboratory predictors to differentiate influenza from dengue and other febrile illnesses in the emergency room
Published in
BMC Infectious Diseases, November 2014
DOI 10.1186/s12879-014-0623-z
Pubmed ID
Authors

Shi-Yu Huang, Ing-Kit Lee, Lin Wang, Jien-Wei Liu, Shih-Chiang Hung, Chien-Chih Chen, Tzu-Yao Chang, Wen-Chi Huang

Abstract

Clinical differentiation of influenza from dengue and other febrile illnesses (OFI) is difficult, and available rapid diagnostic tests have limited sensitivity.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 58 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 25%
Student > Master 9 15%
Student > Bachelor 9 15%
Student > Doctoral Student 6 10%
Student > Ph. D. Student 6 10%
Other 10 17%
Unknown 4 7%
Readers by discipline Count As %
Medicine and Dentistry 26 44%
Agricultural and Biological Sciences 6 10%
Immunology and Microbiology 5 8%
Biochemistry, Genetics and Molecular Biology 4 7%
Unspecified 2 3%
Other 6 10%
Unknown 10 17%

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 09 October 2019.
All research outputs
#9,394,543
of 15,999,693 outputs
Outputs from BMC Infectious Diseases
#2,682
of 5,815 outputs
Outputs of similar age
#139,828
of 308,418 outputs
Outputs of similar age from BMC Infectious Diseases
#304
of 637 outputs
Altmetric has tracked 15,999,693 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,815 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has gotten more attention than average, scoring higher than 50% 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 308,418 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 51% of its contemporaries.
We're also able to compare this research output to 637 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.