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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

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

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2 X users

Citations

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23 Dimensions

Readers on

mendeley
68 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 67 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Master 11 16%
Student > Bachelor 9 13%
Student > Ph. D. Student 7 10%
Student > Doctoral Student 6 9%
Other 10 15%
Unknown 10 15%
Readers by discipline Count As %
Medicine and Dentistry 28 41%
Agricultural and Biological Sciences 6 9%
Immunology and Microbiology 5 7%
Biochemistry, Genetics and Molecular Biology 4 6%
Veterinary Science and Veterinary Medicine 2 3%
Other 7 10%
Unknown 16 24%
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 09 October 2019.
All research outputs
#14,204,846
of 22,771,140 outputs
Outputs from BMC Infectious Diseases
#3,768
of 7,668 outputs
Outputs of similar age
#191,919
of 361,642 outputs
Outputs of similar age from BMC Infectious Diseases
#84
of 196 outputs
Altmetric has tracked 22,771,140 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,668 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 47th percentile – i.e., 47% 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 361,642 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 196 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 52% of its contemporaries.