Imperial College London
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Professor Reiko J. Tanaka

Faculty of Engineering, Department of Bioengineering

Professor of Computational Systems Biology & Medicine
 
 
 
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Contact

 

+44 (0)20 7594 6374r.tanaka Website

 
 
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Location

 

RSM 3.10Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Hurault:2020:10.1101/2020.10.27.20220947,
author = {Hurault, G and Delorieux, V and Kim, Y-M and Ahn, K and Williams, HC and Tanaka, RJ},
doi = {10.1101/2020.10.27.20220947},
title = {Impact of environmental factors in predicting daily severity scores of atopic dermatitis},
url = {http://dx.doi.org/10.1101/2020.10.27.20220947},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - <jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 20% of children worldwide. Although environmental factors including weather and air pollutants have been shown to be associated with AD symptoms, the time-dependent nature of such a relationship has not been adequately investigated.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>This paper aims to assess the short-term impact of weather and air pollutants on AD severity scores.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Using longitudinal data from a published panel study of 177 paediatric patients followed up for 17 months, we developed statistical machine learning models to predict daily AD severity scores for individual study participants. Exposures consisted of daily meteorological variables and concentrations of air pollutants and outcomes were daily recordings of scores for six AD signs. We developed a mixed effect autoregressive ordinal logistic regression model, validated it in a forward-chaining setting, and evaluated the effects of the environmental factors on the predictive performance.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Our model outperformed benchmark models for daily prediction of the AD severity scores. The predictive performance of AD severity scores was not improved by the addition of measured environmental factors. Any potential short-term influence of environmental exposures on AD severity scores was outweighed by the underlying persistence of preceding scores.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our data does not offer enough evidence to support a claim that AD symptoms are associated with wea
AU  - Hurault,G
AU  - Delorieux,V
AU  - Kim,Y-M
AU  - Ahn,K
AU  - Williams,HC
AU  - Tanaka,RJ
DO  - 10.1101/2020.10.27.20220947
PY  - 2020///
TI  - Impact of environmental factors in predicting daily severity scores of atopic dermatitis
UR  - http://dx.doi.org/10.1101/2020.10.27.20220947
ER  -
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