Impact of environmental factors in predicting daily severity scores of atopic dermatitis.

ABSTRACT:

Background

Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 20% of children worldwide. Environmental factors including weather and air pollutants have been shown to be associated with AD symptoms. However, the time-dependent nature of such a relationship has not been adequately investigated. This paper aims to assess whether real-time data on weather and air pollutants can make short-term prediction of AD severity scores.

Methods

Using longitudinal data from a published panel study of 177 paediatric patients followed up daily for 17 months, we developed a statistical machine learning model to predict daily AD severity scores for individual study participants. Exposures consisted of daily meteorological variables and concentrations of air pollutants,

SUBMITTER: Hurault G 

PROVIDER: S-EPMC8099209 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature