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Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection

Overview of attention for article published in BMC Infectious Diseases, November 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
Decision tree for accurate infection timing in individuals newly diagnosed with HIV-1 infection
Published in
BMC Infectious Diseases, November 2017
DOI 10.1186/s12879-017-2850-6
Pubmed ID
Authors

Chris Verhofstede, Katrien Fransen, Annelies Van Den Heuvel, Kristel Van Laethem, Jean Ruelle, Ellen Vancutsem, Karolien Stoffels, Sigi Van den Wijngaert, Marie-Luce Delforge, Dolores Vaira, Laura Hebberecht, Marlies Schauvliege, Virginie Mortier, Kenny Dauwe, Steven Callens

Abstract

There is today no gold standard method to accurately define the time passed since infection at HIV diagnosis. Infection timing and incidence measurement is however essential to better monitor the dynamics of local epidemics and the effect of prevention initiatives. Three methods for infection timing were evaluated using 237 serial samples from documented seroconversions and 566 cross sectional samples from newly diagnosed patients: identification of antibodies against the HIV p31 protein in INNO-LIA, SediaTM BED CEIA and SediaTM LAg-Avidity EIA. A multi-assay decision tree for infection timing was developed. Clear differences in recency window between BED CEIA, LAg-Avidity EIA and p31 antibody presence were observed with a switch from recent to long term infection a median of 169.5, 108.0 and 64.5 days after collection of the pre-seroconversion sample respectively. BED showed high reliability for identification of long term infections while LAg-Avidity is highly accurate for identification of recent infections. Using BED as initial assay to identify the long term infections and LAg-Avidity as a confirmatory assay for those classified as recent infection by BED, explores the strengths of both while reduces the workload. The short recency window of p31 antibodies allows to discriminate very early from early infections based on this marker. BED recent infection results not confirmed by LAg-Avidity are considered to reflect a period more distant from the infection time. False recency predictions in this group can be minimized by elimination of patients with a CD4 count of less than 100 cells/mm3 or without no p31 antibodies. For 566 cross sectional sample the outcome of the decision tree confirmed the infection timing based on the results of all 3 markers but reduced the overall cost from 13.2 USD to 5.2 USD per sample. A step-wise multi assay decision tree allows accurate timing of the HIV infection at diagnosis at affordable effort and cost and can be an important new tool in studies analyzing the dynamics of local epidemics or the effects of prevention strategies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 6 15%
Researcher 5 13%
Student > Bachelor 5 13%
Student > Master 4 10%
Other 3 8%
Other 6 15%
Unknown 10 26%
Readers by discipline Count As %
Unspecified 6 15%
Nursing and Health Professions 3 8%
Biochemistry, Genetics and Molecular Biology 3 8%
Immunology and Microbiology 2 5%
Economics, Econometrics and Finance 2 5%
Other 12 31%
Unknown 11 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 01 December 2021.
All research outputs
#6,355,914
of 23,018,998 outputs
Outputs from BMC Infectious Diseases
#1,962
of 7,723 outputs
Outputs of similar age
#125,980
of 438,547 outputs
Outputs of similar age from BMC Infectious Diseases
#46
of 152 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,723 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 74% 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 438,547 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 70% of its contemporaries.
We're also able to compare this research output to 152 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 69% of its contemporaries.