Risk of severe asthma episodes predicted from fluctuation analysis of airway function View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2005-12

AUTHORS

Urs Frey, Tanja Brodbeck, Arnab Majumdar, D. Robin Taylor, G. Ian Town, Michael Silverman, Béla Suki

ABSTRACT

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy. More... »

PAGES

667

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature04176

DOI

http://dx.doi.org/10.1038/nature04176

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050658491

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16319891


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