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Severe bronchial asthma in children: a review of novel biomarkers used as predictors of the disease

Overview of attention for article published in Journal of Asthma and Allergy, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

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1 news outlet
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1 X user

Citations

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16 Dimensions

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mendeley
40 Mendeley
Title
Severe bronchial asthma in children: a review of novel biomarkers used as predictors of the disease
Published in
Journal of Asthma and Allergy, January 2018
DOI 10.2147/jaa.s149577
Pubmed ID
Authors

Samuel N Uwaezuoke, Adaeze C Ayuk, Joy N Eze

Abstract

Severe asthma or therapy-resistant asthma in children is a heterogeneous disease that affects all age-groups. Given its heterogeneity, precision in diagnosis and treatment has become imperative, in order to achieve better outcomes. If one is thus able to identify specific patient phenotypes and endotypes using the appropriate biomarkers, it will assist in providing the patient with more personalized and appropriate treatment. However, there appears to be a huge diagnostic gap in severe asthma, as there is no single test yet that accurately determines disease phenotype. In this paper, we review the published literature on some of these biomarkers and their possible role in bridging this diagnostic gap. We also highlight the cellular and molecular mechanisms involved in severe asthma, in order to show the basis for the novel biomarkers. Some markers useful for monitoring therapy and assessing airway remodeling in the disease are also discussed. A review of the literature was conducted with PubMed to gather baseline data on the subject. The literature search extended to articles published within the last 40 years. Although biomarkers specific to different severe asthma phenotypes have been identified, progress in their utility remains slow, because of several disease mechanisms, the variation of biomarkers at different levels of inflammation, changes in relying on one test over time (eg, from sputum eosinophilia to blood eosinophilia), and the degree of invasive tests required to collect biomarkers, which limits their applicability in clinical settings. In conclusion, several biomarkers remain useful in recognizing various asthma phenotypes. However, due to disease heterogeneity, identification and utilization of ideal and defined biomarkers in severe asthma are still inconclusive. The development of novel serum/sputum-based biomarker panels with enhanced sensitivity and specificity may lead to prompt diagnosis of the disease in the future.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 28%
Student > Ph. D. Student 3 8%
Student > Postgraduate 3 8%
Student > Bachelor 2 5%
Professor 2 5%
Other 7 18%
Unknown 12 30%
Readers by discipline Count As %
Medicine and Dentistry 20 50%
Immunology and Microbiology 2 5%
Environmental Science 1 3%
Business, Management and Accounting 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 2 5%
Unknown 13 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 08 September 2018.
All research outputs
#3,195,255
of 23,016,919 outputs
Outputs from Journal of Asthma and Allergy
#81
of 463 outputs
Outputs of similar age
#72,973
of 442,344 outputs
Outputs of similar age from Journal of Asthma and Allergy
#2
of 5 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 463 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done well, scoring higher than 81% 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 442,344 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.