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Differentiating secondary from primary dengue using IgG to IgM ratio in early dengue: an observational hospital based clinico-serological study from North India

Overview of attention for article published in BMC Infectious Diseases, November 2016
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Title
Differentiating secondary from primary dengue using IgG to IgM ratio in early dengue: an observational hospital based clinico-serological study from North India
Published in
BMC Infectious Diseases, November 2016
DOI 10.1186/s12879-016-2053-6
Pubmed ID
Authors

Khalid Hamid Changal, Ab Hameed Raina, Adnan Raina, Manzoor Raina, Rehana Bashir, Muzamil Latief, Tanveer Mir, Qayum Hamid Changal

Abstract

Secondary dengue causes more severe disease than the primary. Early on, it is important to differentiate the two. We tried to find important clinical and laboratory differences between the two for the purpose of early differentiation. One hundred fourteen patients confirmed on reverse transcriptase-polymerase chain reaction (RT PCR) were studied. On day 2 of illness IgM and IgG indices were studied for calculation of IgG/IgM ratio. A one-step immunochromatographic assay was used for classification of patients into primary and secondary dengue. Patient characteristics were also studied. Dengue serotype 1 was the most common found in 60.5% patients. 66.7% (76 patients) had secondary dengue. Secondary dengue cases had a higher mean temperature (101.56 ± 1.55 vs. 100.79 ± 1.25,°F, p 0.015), lower platelet counts (50.51 ± 38.91 vs. 100.45 ± 38.66, x 10(3)/micl, p <0.0001) and a significantly higher percentage of Dengue hemorrhagic fever/Dengue shock syndrome (38.2% vs. 2.6%, p <0.0001). In early phase of dengue NS1 and PCR were found to be better tests for diagnosis and later IgM is better. The IgG/IgM ratio of ≥ 1.10 had a sensitivity of 100%, specificity of 97.4% and accuracy of 67.5% in differentiating secondary from primary dengue. Early on in the clinical course, IgG/ IgM ratio can play an important role to differentiate the two. We found the ratio of ≥ 1.10 to be the best cut off for the same.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 74 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 24%
Student > Bachelor 15 20%
Student > Master 12 16%
Unspecified 10 13%
Student > Postgraduate 6 8%
Other 14 19%
Readers by discipline Count As %
Medicine and Dentistry 22 29%
Biochemistry, Genetics and Molecular Biology 15 20%
Unspecified 13 17%
Immunology and Microbiology 10 13%
Agricultural and Biological Sciences 7 9%
Other 8 11%

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 06 December 2016.
All research outputs
#7,573,070
of 8,734,076 outputs
Outputs from BMC Infectious Diseases
#3,458
of 3,855 outputs
Outputs of similar age
#242,556
of 299,034 outputs
Outputs of similar age from BMC Infectious Diseases
#146
of 195 outputs
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We're also able to compare this research output to 195 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.