Background Fraction of exhaled nitric oxide (Feno), a marker of airway inflammation, has been proposed to be useful for asthma management, but conclusions are inconsistent. This might be due to the failure of mean statistics to characterize individual variability in Feno values, which is possibly a better indicator of asthma control than single measurements. Objective We characterized fractal fluctuations in daily Feno values over time and the relationship between Feno values and symptom scores. We investigated whether these are associated with asthma severity, control, and exacerbation risk. Methods Daily Feno values and symptom scores over 192 days in 41 atopic asthmatic children from the Childhood Asthma Respiratory Inflammatory Status Monitoring study were analyzed. Two methods of time-series analysis were used: detrended fluctuation analysis to quantify fractal patterns in fluctuations in daily Feno values (α value) and cross-correlation to quantify the strength of the relationship between daily Feno values and symptom scores. The associations of α values and cross-correlation with markers of asthma severity and control were assessed by means of regression analysis. Results Daily fluctuations in Feno values exhibited fractal-type long-range correlations. Those subjects receiving higher doses of inhaled corticosteroids at study entry had a significantly lower α value, corresponding to more random fluctuations in Feno values in those with greater inhaled corticosteroid need. The cross-correlation between Feno values and symptom scores was significantly higher in those subjects who had exacerbations. Conclusions Fluctuation in Feno values and their cross-correlation to symptom scores contains information on asthma severity and control. Methods that quantify the complexity of asthma over time might assist in identifying asthmatic subjects with concordance between eosinophilic inflammation and symptoms and thus increased exacerbation risk.

Fluctuation phenotyping based on daily fraction of exhaled nitric oxide values in asthmatic children.

BARALDI, EUGENIO;CARRARO, SILVIA;
2011

Abstract

Background Fraction of exhaled nitric oxide (Feno), a marker of airway inflammation, has been proposed to be useful for asthma management, but conclusions are inconsistent. This might be due to the failure of mean statistics to characterize individual variability in Feno values, which is possibly a better indicator of asthma control than single measurements. Objective We characterized fractal fluctuations in daily Feno values over time and the relationship between Feno values and symptom scores. We investigated whether these are associated with asthma severity, control, and exacerbation risk. Methods Daily Feno values and symptom scores over 192 days in 41 atopic asthmatic children from the Childhood Asthma Respiratory Inflammatory Status Monitoring study were analyzed. Two methods of time-series analysis were used: detrended fluctuation analysis to quantify fractal patterns in fluctuations in daily Feno values (α value) and cross-correlation to quantify the strength of the relationship between daily Feno values and symptom scores. The associations of α values and cross-correlation with markers of asthma severity and control were assessed by means of regression analysis. Results Daily fluctuations in Feno values exhibited fractal-type long-range correlations. Those subjects receiving higher doses of inhaled corticosteroids at study entry had a significantly lower α value, corresponding to more random fluctuations in Feno values in those with greater inhaled corticosteroid need. The cross-correlation between Feno values and symptom scores was significantly higher in those subjects who had exacerbations. Conclusions Fluctuation in Feno values and their cross-correlation to symptom scores contains information on asthma severity and control. Methods that quantify the complexity of asthma over time might assist in identifying asthmatic subjects with concordance between eosinophilic inflammation and symptoms and thus increased exacerbation risk.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2481098
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