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Letter

Nature 438, 667-670 (1 December 2005) | doi:10.1038/nature04176; Received 25 June 2005; Accepted 31 August 2005

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

Urs Frey1, Tanja Brodbeck1, Arnab Majumdar2, D. Robin Taylor3, G. Ian Town3, Michael Silverman4 & Béla Suki2

  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).

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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 possible2, 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 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.

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