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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
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Data Structure of Clinical Research

Authors: Kozhyna Olga; Pihnastyi Oleg;

Data Structure of Clinical Research

Abstract

Bronchial asthma is one of the most common respiratory pathologies in children, characterized by rising incidence around the world. Early disease onset, severe clinical signs of bronchial asthma, the ineffectiveness of high doses of hormone therapy reduce the quality of life in patients and lead to disability. Analysis of bronchial asthma heterogeneity is now possible in virtue of computer technology and big data processing onrush. The information on 70 children suffering from bronchial asthma and 20 children from the control group was analyzed in this study. Gender, age, duration of disease, associated diseases, family history of allergic diseases, clinical blood and urine test, spirography and blood immunoassay results, total IgE, thymic stromal lymphopoietin and results of skin allergy tests were taken into account.

{"references": ["1.\tGlobal_Atlas_of_Asthma. (2013).196. www.eaaci.org", "2.\tHafkamp-de Groen E, Lingsma HF, Caudri D, Levie D, Wijga A, Koppelman GH, et al. Predicting asthma in preschool children with asthma-like symptoms: validating and updating the PIAMA risk score. J Allergy Clin Immunol. 2013;132(6):1303\u20131310.", "3.\tO'Byrne PM, Pedersen S, Lamm CJ, Tan WC, Busse WW. Severe exacerbations and decline in lung function in asthma. Am J Respir Crit Care Med. 2009;179(1):19\u201324.", "4.\tFitzpatrick AM, Teague WG. Severe Asthma in Children: Insights from the National Heart, Lung, and Blood Institute's Severe Asthma Research Program. Pediatr Allergy Immunol Pulmonol. 2010; 23(2):131-8."]}

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Keywords

bronchial asthma, severity, prognostication

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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