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Meta-analysis of biomarkers for severe dengue infections

Overview of attention for article published in PeerJ, September 2017
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Title
Meta-analysis of biomarkers for severe dengue infections
Published in
PeerJ, September 2017
DOI 10.7717/peerj.3589
Pubmed ID
Authors

Kuan-Meng Soo, Bahariah Khalid, Siew-Mooi Ching, Chau Ling Tham, Rusliza Basir, Hui-Yee Chee

Abstract

Dengue viral infection is an acute infection that has the potential to have severe complications as its major sequela. Currently, there is no routine laboratory biomarker with which to predict the severity of dengue infection or monitor the effectiveness of standard management. Hence, this meta-analysis compared biomarker levels between dengue fever (DF) and severe dengue infections (SDI) to identify potential biomarkers for SDI. Data concerning levels of cytokines, chemokines, and other potential biomarkers of DF, dengue hemorrhagic fever, dengue shock syndrome, and severe dengue were obtained for patients of all ages and populations using the Scopus, PubMed, and Ovid search engines. The keywords "(IL1* or IL-1*) AND (dengue*)" were used and the same process was repeated for other potential biomarkers, according to Medical Subject Headings terms suggested by PubMed and Ovid. Meta-analysis of the mean difference in plasma or serum level of biomarkers between DF and SDI patients was performed, separated by different periods of time (days) since fever onset. Subgroup analyses comparing biomarker levels of healthy plasma and sera controls, biomarker levels of primary and secondary infection samples were also performed, as well as analyses of different levels of severity and biomarker levels upon infection by different dengue serotypes. Fifty-six studies of 53 biomarkers from 3,739 dengue cases (2,021 DF and 1,728 SDI) were included in this meta-analysis. Results showed that RANTES, IL-7, IL-8, IL-10, IL-18, TGF-b, and VEGFR2 levels were significantly different between DF and SDI. IL-8, IL-10, and IL-18 levels increased during SDI (95% CI, 18.1-253.2 pg/mL, 3-13 studies, n = 177-1,909, I(2) = 98.86%-99.75%). In contrast, RANTES, IL-7, TGF-b, and VEGFR2 showed a decrease in levels during SDI (95% CI, -3238.7 to -3.2 pg/mL, 1-3 studies, n = 95-418, I(2) = 97.59%-99.99%). Levels of these biomarkers were also found to correlate with the severity of the dengue infection, in comparison to healthy controls. Furthermore, the results showed that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 display peak differences between DF and SDI during or before the critical phase (day 4-5) of SDI. This meta-analysis suggests that IL-7, IL-8, IL-10, TGF-b, and VEGFR2 may be used as potential early laboratory biomarkers in the diagnosis of SDI. This can be used to predict the severity of dengue infection and to monitor the effectiveness of treatment. Nevertheless, methodological and reporting limitations must be overcome in future research to minimize variables that affect the results and to confirm the findings.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 19%
Student > Ph. D. Student 12 13%
Researcher 11 12%
Student > Bachelor 10 11%
Student > Doctoral Student 4 4%
Other 12 13%
Unknown 23 26%
Readers by discipline Count As %
Immunology and Microbiology 20 22%
Medicine and Dentistry 17 19%
Agricultural and Biological Sciences 9 10%
Biochemistry, Genetics and Molecular Biology 6 7%
Nursing and Health Professions 3 3%
Other 8 9%
Unknown 26 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 November 2017.
All research outputs
#14,304,074
of 23,006,268 outputs
Outputs from PeerJ
#8,132
of 13,412 outputs
Outputs of similar age
#174,538
of 316,182 outputs
Outputs of similar age from PeerJ
#234
of 355 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,412 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 316,182 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 355 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.