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

Authors Ribeiro CO, Faria ACD, Lopes AJ, de Melo PL

Received 10 May 2018

Accepted for publication 30 July 2018

Published 11 October 2018 Volume 2018:13 Pages 3281—3295

DOI https://doi.org/10.2147/COPD.S173686

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 2

Editor who approved publication: Dr Richard Russell


Caroline Oliveira Ribeiro,1 Alvaro Camilo Dias Faria,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, Brazil

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.

Keywords: COPD, oscillation mechanics, smoking, respiratory modeling, integer-order modeling, respiratory impedance

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