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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 no...

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Detalles Bibliográficos
Autores principales: Ribeiro, Caroline Oliveira, Lopes, Agnaldo José, de Melo, Pedro Lopes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9081189/
https://www.ncbi.nlm.nih.gov/pubmed/35547780
http://dx.doi.org/10.2147/COPD.S353912
Descripción
Sumario: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 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.