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Diagnostic ‘omics’ for active tuberculosis

Overview of attention for article published in BMC Medicine, March 2016
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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 (87th percentile)

Mentioned by

blogs
1 blog
twitter
11 tweeters

Citations

dimensions_citation
49 Dimensions

Readers on

mendeley
187 Mendeley
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Title
Diagnostic ‘omics’ for active tuberculosis
Published in
BMC Medicine, March 2016
DOI 10.1186/s12916-016-0583-9
Pubmed ID
Authors

Carolin T. Haas, Jennifer K. Roe, Gabriele Pollara, Meera Mehta, Mahdad Noursadeghi

Abstract

The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.

Twitter Demographics

The data shown below were collected from the profiles of 11 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 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
South Africa 1 <1%
Brazil 1 <1%
Thailand 1 <1%
Colombia 1 <1%
Unknown 181 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 25%
Student > Master 32 17%
Student > Ph. D. Student 25 13%
Student > Bachelor 18 10%
Student > Doctoral Student 14 7%
Other 28 15%
Unknown 23 12%
Readers by discipline Count As %
Medicine and Dentistry 56 30%
Agricultural and Biological Sciences 32 17%
Biochemistry, Genetics and Molecular Biology 30 16%
Immunology and Microbiology 24 13%
Nursing and Health Professions 5 3%
Other 18 10%
Unknown 22 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 07 December 2016.
All research outputs
#1,463,884
of 15,916,297 outputs
Outputs from BMC Medicine
#1,084
of 2,485 outputs
Outputs of similar age
#33,113
of 267,557 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 15,916,297 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,485 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.9. This one has gotten more attention than average, scoring higher than 56% 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 267,557 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 87% 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