Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity.

Purpose: This research examines the emerging role of respiratory oscillometry associated with integer (InOr) and fractional order (FrOr) respiratory models in the context of groups of patients with increasing severity. The contributions to our understanding of the respiratory abnormalities along the course of increasing COPD severity and the diagnostic use of this method were also evaluated. Patients and Methods: Forty-five individuals with no history of smoking or pulmonary diseases (control group) and 141 individuals with diagnoses of COPD were studied, being classified into 45 mild, 42 moderate, 36 severe and 18 very severe cases. Results: This study has shown initially that the course of increasing COPD severity was adequately described by the model parameters. This resulted in significant and consistent correlations among these parameters and spirometric indexes. Additionally, this evaluation enhanced our understanding of the respiratory abnormalities in different COPD stages. The diagnostic accuracy analyses provided evidence that hysteresivity, obtained from FrOr modeling, allowed a highly accurate identification in patients with mild changes [area under the receiver operator characteristic curve (AUC)= 0.902]. Similar analyses in groups of moderate and severe patients showed that peripheral resistance, derived from InOr modeling, provided the most accurate parameter (AUC=0.898 and 0.998, respectively), while in very severe patients, traditional, InOr and FrOr parameters were able to reach high diagnostic accuracy (AUC>0.9). Conclusion: InOr and FrOr modeling improved our knowledge of the respiratory abnormalities along the course of increasing COPD severity. In addition, the present study provides evidence that these models may contribute in the diagnosis of COPD. Respiratory oscillometry exams require only tidal breathing and are easy to perform. Taken together, these practical considerations and the results of the present study suggest that respiratory oscillometry associated with InOr and FrOr models may help to improve lung function tests in COPD.

Forced oscillation technique for early detection of the effects of smoking and COPD: contribution of fractional-order modeling.

PURPOSE: The aim of the present study was to evaluate the performance of the forced oscillation technique (FOT) for the early diagnosis of the effects of smoking and COPD. The contributions of the integer-order (InOr) and fractional-order (FrOr) models were also evaluated. PATIENTS AND METHODS: In total, 120 subjects were analyzed: 40 controls, 40 smokers (20.3±9.3 pack-years) and 40 patients with mild COPD. RESULTS: Initially, it was observed that traditional FOT parameters and the InOr and FrOr models provided a consistent description of the COPD pathophysiology. Mild COPD introduced significant increases in the FrOr inertance, damping factor and hysteresivity (P<0.0001). These parameters were significantly correlated with the spirometric parameters of central and small airway obstruction (P<0.0001). The diagnostic accuracy analyses indicated that FOT parameters and InOr modeling may adequately identify these changes (area under the receiver operating characteristic curve - AUC >0.8). The use of FrOr modeling significantly improved this process (P<0.05), allowing the early diagnosis of smokers and patients with mild COPD with high accuracy (AUC >0.9). CONCLUSION: FrOr modeling improves our knowledge of modifications that occur in the early stages of COPD. Additionally, the findings of the present study provide evidence that these models may play an important role in the early diagnosis of COPD, which is crucial for improving the clinical management of the disease.