Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Frey, Urs; Brodbeck, Tanja; Majumdar, Arnab; Taylor, D Robin; Town, G Ian; Silverman, Michael; Suki, Béla (2005). Risk of severe asthma episodes predicted from fluctuation analysis of airway function. Nature, 438(7068), pp. 667-70. London: Macmillan Journals Ltd. 10.1038/nature04176

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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.

Item Type:	Journal Article (Original Article)
Division/Institute:	04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Paediatric Medicine
UniBE Contributor:	Frey, Urs Peter
ISSN:	0028-0836
Publisher:	Macmillan Journals Ltd.
Language:	English
Submitter:	Anette van Dorland
Date Deposited:	04 Oct 2013 15:12
Last Modified:	05 Dec 2022 14:22
Publisher DOI:	10.1038/nature04176
PubMed ID:	16319891
Web of Science ID:	000233593100050
URI:	https://boris.unibe.ch/id/eprint/31896 (FactScience: 196669)