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Methods to discriminate primary from secondary dengue during acute symptomatic infection

Overview of attention for article published in BMC Infectious Diseases, August 2018
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Title
Methods to discriminate primary from secondary dengue during acute symptomatic infection
Published in
BMC Infectious Diseases, August 2018
DOI 10.1186/s12879-018-3274-7
Pubmed ID
Authors

Thi Hanh Tien Nguyen, Hannah E. Clapham, Khanh Lam Phung, Thanh Kieu Nguyen, The Trung DInh, Than Ha Quyen Nguyen, Van Ngoc Tran, Stephen Whitehead, Cameron Simmons, Marcel Wolbers, Bridget Wills

Abstract

Dengue virus infection results in a broad spectrum of clinical outcomes, ranging from asymptomatic infection through to severe dengue. Although prior infection with another viral serotype, i.e. secondary dengue, is known to be an important factor influencing disease severity, current methods to determine primary versus secondary immune status during the acute illness do not consider the rapidly evolving immune response, and their accuracy has rarely been evaluated against an independent gold standard. Two hundred and ninety-three confirmed dengue patients were classified as experiencing primary, secondary or indeterminate infections using plaque reduction neutralisation tests performed 6 months after resolution of the acute illness. We developed and validated regression models to differentiate primary from secondary dengue on multiple acute illness days, using Panbio Indirect IgG and in-house capture IgG and IgM ELISA measurements performed on over 1000 serial samples obtained during acute illness. Cut-offs derived for the various parameters demonstrated progressive change (positively or negatively) by day of illness. Using these time varying cut-offs it was possible to determine whether an infection was primary or secondary on single specimens, with acceptable performance. The model using Panbio Indirect IgG responses and including an interaction with illness day showed the best performance throughout, although with some decline in performance later in infection. Models based on in-house capture IgG levels, and the IgM/IgG ratio, also performed well, though conversely performance improved later in infection. For all assays, the best fitting models estimated a different cut-off value for different days of illness, confirming how rapidly the immune response changes during acute dengue. The optimal choice of assay will vary depending on circumstance. Although the Panbio Indirect IgG model performs best early on, the IgM/IgG capture ratio may be preferred later in the illness course.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Master 8 21%
Student > Bachelor 3 8%
Other 2 5%
Student > Ph. D. Student 2 5%
Other 4 11%
Unknown 10 26%
Readers by discipline Count As %
Immunology and Microbiology 8 21%
Medicine and Dentistry 6 16%
Nursing and Health Professions 2 5%
Biochemistry, Genetics and Molecular Biology 2 5%
Arts and Humanities 2 5%
Other 4 11%
Unknown 14 37%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 August 2018.
All research outputs
#10,190,552
of 13,350,484 outputs
Outputs from BMC Infectious Diseases
#3,157
of 4,973 outputs
Outputs of similar age
#185,053
of 267,903 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
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