Airway impedance entropy and exacerbations in severe asthma

Abstract

Variability of peak flow measurements has been related to clinical outcomes in asthma. We hypothesised that the entropy, or information content, of airway impedance over short time scales may predict asthma exacerbation frequency.66 patients with severe asthma and 30 healthy control subjects underwent impulse oscillometry at baseline and following bronchodilator administration. On each occasion, airway impedance parameters were measured at 0.2-s intervals for 150 s, yielding a time series that was then subjected to sample entropy (SampEn) analysis.Airway impedance and SampEn of impedance were increased in asthmatic patients compared with healthy controls. In a logistic regression model, SampEn of the resistance at 5 Hz minus the resistance at 20 Hz, a marker of the fluctuation of the heterogeneity of airway constriction over time, was the variable most strongly associated with the frequent exacerbation phenotype (OR 3.23 for every 0.1 increase in SampEn).Increased airway impedance and SampEn of impedance are associated with the frequent exacerbation phenotype. Prospective studies are required to assess their predictive value.KEYWORDS: Airflow obstruction, asthma, entropy, oscillometry A cute exacerbations of asthma account for much of the morbidity and mortality associated with this condition [1]. However, there is no currently available biomarker that can accurately predict the risk of future exacerbations. Previous studies have suggested that a geometrically self-similar airway tree may confer increased risk of asthma exacerbations and that fatal asthma is associated with a reduction in the structural complexity of the airway tree [2]. Similarly, the ventilation heterogeneity observed in asthma follows power law behaviour, which predicts catastrophic closure of small airways [3]. Therefore, characterising structural complexity may have utility in predicting asthma exacerbations.It has been speculated that the temporal variability in lung function may also exhibit self-similarity at multiple time scales [4]. This would suggest that monitoring lung function over short time scales may provide insights into lung function variability over longer time scales of weeks to months, thus providing a more practical predictive tool for exacerbations. A number of tools have been utilised to characterise time series properties of physiological signals, including those that predict scaling and power law behaviour of information over multiple time scales and those that predict the probability of information repeating itself within a time series [5,6]. Fluctuations and power law behaviour observed in a time series of lung function measurements such as peak expiratory flow (PEF) may predict poor asthma control or exacerbations [7,8]. THAMRIN et al [9] found that the degree of long-range correlation (self-similarity at different temporal length scales) in PEF measurements appeared to provide additional predictive information with respect to exacerbations in mildto-moderate asthma, but less so in severe asthma.The force...

Clinical significance of small airway obstruction markers in patients with asthma

“…It is therefore possible that the associations that were observed in previous studies were at least partly related to the effect of proximal airway tone impacting upon the heterogeneity of distal airway calibre. Indeed, both we and others have previously found that pre‐bronchodilator physiological measurements correlate more strongly with asthma outcomes than post‐bronchodilator measurements.…”

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