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Elayne Moura Teixeira,1 Caroline Oliveira Ribeiro,1 Agnaldo José Lopes,2,3 Pedro Lopes de Melo1,4 1Biomedical Instrumentation Laboratory, Institute of Biology and Faculty of Engineering, State University of Rio de Janeiro, Rio de Janeiro, Brazil; 2Pulmonary Function Laboratory, Pedro Ernesto University Hospital, Faculty of Medical Sciences, State University of Rio de Janeiro, Rio de Janeiro, Brazil; 3Pulmonary Rehabilitation Laboratory, Augusto Motta University Center, Rio de Janeiro, Brazil; 4Laboratory of Clinical and Experimental Research in Vascular Biology - Biomedical Center, State University of Rio de Janeiro, Rio de Janeiro, BrazilCorrespondence: Pedro Lopes de Melo, Rua São Francisco Xavier 524, Pavilhão Haroldo Lisboa da Cunha, Sala 104, Maracanã, Rio de Janeiro, RJ, 20550-013, Brazil, Tel +55-21-2334-0705, Email plopes@uerj.brPurpose: 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 Glittre‑ADL 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.Keywords: asthma-COPD overlap, emphysema, chronic bronchitis, respiratory impedance, handgrip analysis, Glittre-ADL test, forced oscillation technique, bronchodilator response

Caroline Oliveira Ribeiro,1 Agnaldo José Lopes,2,3 Pedro Lopes de Melo1 1Biomedical Instrumentation Laboratory, Institute of Biology and Faculty of Engineering, State University of Rio de Janeiro, Rio de Janeiro, Brazil; 2Pulmonary Function Laboratory, State University of Rio de Janeiro, Rio de Janeiro, Brazil; 3Pulmonary Rehabilitation Laboratory, Augusto Motta University Center, Rio de Janeiro, BrazilCorrespondence: Pedro Lopes de Melo, Rua São Francisco Xavier 524, Pavilhão Haroldo Lisboa da Cunha, Sala 104, Maracanã, Rio de Janeiro, 20550-013, Brazil, Tel +55-21-2334-0705, Email plopes@uerj.brPurpose: 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 Glittre‑ADL 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.Keywords: chronic obstructive pulmonary disease, COPD physiopathology, forced oscillation technique, respiratory impedance, Glittre-ADL test, handgrip strength, exercise limitation