1. Paediatric Respiratory Medicine, Department of Paediatrics, University Hospital of Berne, Inselspital 3010 Berne, Switzerland
2. Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
3. Faculty of Medicine, Dunedin/Christchurch Schools of Medicine, University of Otago, New Zealand
4. Institute for Lung Health, Leicester University, Leicester LE2 7LX, UK

Correspondence to: Urs Frey¹ Correspondence and requests for materials should be addressed to U.F. (Email: urs.frey@insel.ch).

Abstract

Asthma is an increasing health problem worldwide¹, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible^{2, 3}. 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 trial⁴. 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 ₂-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.

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