Multiscale Entropy Reveals Reduced Airflow Complexity in Chronic Obstructive Pulmonary Disease: Associations with Spirometry and Diagnostic Utility.
cross_sectional · Level IV
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- Also identified by DOI 10.1007/s10439-026-04330-3.
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Abstract
To investigate the ability of multiscale entropy (MSE) methods to characterize alterations in airflow dynamics in chronic obstructive pulmonary disease (COPD) and to evaluate their associations with lung function and diagnostic performance. Spontaneous airflow signals were recorded during 150 s from 29 controls and 25 patients with COPD. Signal complexity was quantified using MSE, refined composite MSE (RCMSE), refined composite multiscale fuzzy entropy (RCMFE), and multiscale permutation entropy (MPE). The area under the entropy curve was calculated over predefined scale ranges (S<sub>0-50</sub>, S<sub>50-100</sub>, and S<sub>0-100</sub>), and entropy at τ = 1 was also analyzed. Associations with spirometry and respiratory resistance (R6) were evaluated, and diagnostic performance was assessed using ROC analysis. COPD patients showed a consistent reduction in airflow complexity across all entropy measures. Entropy indices were positively associated with spirometric parameters and inversely associated with R6, indicating progressive loss of complexity with increasing airway obstruction. The strongest correlations were observed at τ = 1, particularly with R6. Among multiscale indices, S<sub>0-50</sub> showed the strongest associations with lung function, suggesting predominant involvement of short-term airflow dynamics, consistent with small airway abnormalities in COPD. ROC analysis demonstrated high diagnostic accuracy for MSE and RCMSE (AUC > 0.90 for S<sub>0-50</sub> and SampEn<sub>1</sub>), with comparable performance for MPE and lower accuracy for RCMFE. Multiscale entropy analysis of spontaneous airflow provides a sensitive, noninvasive approach for detecting and characterizing respiratory dysfunction in COPD. These methods capture clinically relevant alterations in airflow dynamics and offer complementary information to conventional lung function tests. Further studies are warranted to validate these findings and enhance their clinical applicability.