Respiratory Oscillometry and Functional Performance in Different COPD Phenotypes.

Purpose: Chronic obstructive pulmonary disease (COPD) phenotypes may introduce different characteristics that need to be known to improve treatment. Respiratory oscillometry provides a detailed analysis and may offer insight into the pathophysiology of COPD. In this paper, we used this method to evaluate the differences in respiratory mechanics of COPD phenotypes. Patients and Methods: This study investigated a sample of 83 volunteers, being divided into control group (CG = 20), emphysema (n = 23), CB (n = 20) and asthma-COPD overlap syndrome (ACOS, n = 20). These analyses were performed before and after bronchodilator (BD) use. Functional capacity was evaluated using the Glittre­ADL test, handgrip strength and respiratory pressures. Results: Initially it was observed that oscillometry provided a detailed description of the COPD phenotypes, which was consistent with the involved pathophysiology. A correlation between oscillometry and functional capacity was observed (r=-0.541; p = 0.0001), particularly in the emphysema phenotype (r = -0.496, p = 0.031). BD response was different among the studied phenotypes. This resulted in an accurate discrimination of ACOS from CB [area under the receiver operating curve (AUC) = 0.84] and emphysema (AUC = 0.82). Conclusion: These results offer evidence that oscillatory indices may enhance the comprehension and identification of COPD phenotypes, thereby potentially improving the support provided to these patients.

Respiratory Oscillometry in Chronic Obstructive Pulmonary Disease: Association with Functional Capacity as Evaluated by Adl Glittre Test and Hand Grip Strength Test.

Purpose: Respiratory oscillometry has emerged as a powerful method for detecting respiratory abnormalities in COPD. However, this method has not been widely introduced into clinical practice. This limitation arises, at least in part, because the clinical meaning of the oscillometric parameters is not clear. In this paper, we evaluated the association of oscillometry with functional capacity and its ability to predict abnormal functional capacity in COPD. Patients and Methods: This cross-sectional study investigated a control group formed by 30 healthy subjects and 30 outpatients with COPD. The subjects were classified by the Glittre­ADL test and handgrip strength according to the functional capacity. Results: This study has shown initially that subjects with abnormal functional capacity had a higher value for resistance (p < 0.05), reactance area (Ax, p < 0.01), impedance modulus (Z4, p < 0.05), and reduced dynamic compliance (Cdyn, p < 0.05) when compared with subjects with normal functional capacity. This resulted in significant and consistent correlations among resistive oscillometric parameters (R=-0.43), Cdyn (R=-0.40), Ax (R = 0.42), and Z4 (R = 0.41) with exercise performance. Additionally, the effects of exercise limitation in COPD were adequately predicted, as evaluated by the area under the curve (AUC) obtained by receiver operating characteristic analysis. The best parameters for this task were R4-R20 (AUC = 0.779) and Ax (AUC = 0.752). Conclusion: Respiratory oscillometry provides information related to functional capacity in COPD. This method is also able to predict low exercise tolerance in these patients. These findings elucidate the physiological and clinical meaning of the oscillometric parameters, improving the interpretation of these parameters in COPD patients.

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.