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Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Overview of attention for article published in BMC Infectious Diseases, April 2012
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  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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4 X users

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30 Mendeley
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Title
Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection
Published in
BMC Infectious Diseases, April 2012
DOI 10.1186/1471-2334-12-88
Pubmed ID
Authors

Jörg Schüpbach, Leslie R Bisset, Martin D Gebhardt, Stephan Regenass, Philippe Bürgisser, Meri Gorgievski, Thomas Klimkait, Corinne Andreutti, Gladys Martinetti, Christoph Niederhauser, Sabine Yerly, Stefan Pfister, Detlev Schultze, Marcel Brandenberger, Franziska Schöni-Affolter, Alexandra U Scherrer, Huldrych F Günthard, Swiss HIV Cohort Study

Abstract

Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Portugal 1 3%
Argentina 1 3%
Unknown 27 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 30%
Student > Bachelor 5 17%
Student > Ph. D. Student 4 13%
Student > Master 2 7%
Other 2 7%
Other 4 13%
Unknown 4 13%
Readers by discipline Count As %
Medicine and Dentistry 9 30%
Agricultural and Biological Sciences 3 10%
Mathematics 2 7%
Immunology and Microbiology 2 7%
Unspecified 1 3%
Other 7 23%
Unknown 6 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 14 April 2012.
All research outputs
#13,128,940
of 22,664,267 outputs
Outputs from BMC Infectious Diseases
#3,142
of 7,636 outputs
Outputs of similar age
#88,445
of 161,626 outputs
Outputs of similar age from BMC Infectious Diseases
#33
of 95 outputs
Altmetric has tracked 22,664,267 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,636 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 57% 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 161,626 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 95 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 62% of its contemporaries.