Respiratory pattern complexity in newly-diagnosed asthmatic patients.

BACKGROUND

The intensity of respiratory symptoms and expiratory airflow limitations in asthma fluctuate over time. Some studies have reported variable complexity of the respiratory patterns in asthmatic patients. Thus, we conducted a novel study to assess the correlation between asthma severity and breathing pattern dynamics in newly-diagnosed asthmatic patients.

METHODS

A total of 20 newly-diagnosed asthmatic patients (7 male, 13 female) and 20 healthy cases (11 male, 9 female) were included. The respiratory patterns of all participants and the asthma severity for asthmatic patients were measured using a spirometer (before and after a bronchodilator exposure) and airflow recorder, respectively. The peak-to-peak intervals and the amplitude of peaks were considered as the inter-breath interval (IBI) and lung volume (LV) series. The Detrended Fluctuation Analysis (DFA), Sample Entropy (SampEn), Multi-scale Entropy (MSE), short-term (SD1) and long-term (SD2) variability, and IBI and LV Cross-Sample Entropy of the respiratory pattern dynamics were calculated using MATLAB (Mathwork, USA).

RESULTS

Asthma patients showed notable increase in the average of sample entropy in both IBI and LV parameters (p = 0.025 and p = 0.018, respectively) and also decreased synchronization between IBI and LV (p = 0.042). The multi-scale sample entropy of both IBI and LV was significantly higher in asthmatic patients (p < 0.05). Furthermore, SD1 and SD2 were higher in the patients with asthma (p < 0.05). Significant correlations were detected between spirometric (forced expiratory flow (FEF) change, pre FEF, pre forced expiratory volume in one second (FEV1) / forced vital capacity (FVC), FVC change) and respiratory pattern (mean-IBI, mean-LV, mean-respiratory rate (RR), coefficient of variation (CV)-IBI, CV-LV, cross-sample entropy) parameters (p < 0.05). Furthermore, we identified a negative correlation between CV of IBI and asthma severity (r = -0.52, p = 0.021).

CONCLUSION

Here, we took a novel approach and observed increased irregularity (more complexity) in the breathing pattern of patients newly-diagnosed with asthma. Remarkable correlations were detected between breathing complexity markers and spirometric indices along with disease severity in asthmatic patients. Thus, our data suggests respiratory pattern indices could be utilized as an indicator of asthma and its severity. However, more clinical data are required to support this conclusion.