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DOI: 10.1055/s-0044-1782530
Validation of a Portable Respiratory Monitoring System for the Diagnosis of Obstructive Sleep Apnea in Patients with Chronic Obstructive Pulmonary Disease: A Crossectional Study
Funding Source This work was supported by a grant (grant 1783-4.01/2016) from the Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco (FACEPE).Abstract
Introduction Portable respiratory monitoring (PM) has been used to diagnose obstructive sleep apnea (OSA) in the general population. However, its validation in patients with both OSA and chronic obstructive pulmonary disease (COPD), remains unclear.
Objective The aim of the study was to validate PM for the diagnosis of OSA in patients with COPD.
Materials and Methods In this crossectional study, COPD patients were submitted simultaneously to polysomnography (PSG) and PM. Moreover, the risk for OSA was verified by the Berlin, NoSAS, and STOP-BANG questionnaires. Sensitivity, specificity, positive predictive value, and negative predictive value for PM were calculated for the cutoff points of the hypopnea apnea index (AHI) of 5, 15, and 30 events/hour, as well as for the questionnaires. The Bland-Altman test and correlation analyses between the AHI of the PSG and PM were performed.
Results A total of 103 patients were evaluated (age 67.5 ± 9.9 years, 60% men). The STOP-BANG questionnaire had the highest sensitivity for OSA diagnosis, at 94.4% (72.7–99.9%). The sensitivity of PM decreased (87.0, 66.7, and 44.4%), and the specificity increased 40.0, 78.6, and 100.0%) as the AHI cutoff point increased from 5, 15, and 30. The Bland-Altman test indicated good limits of agreement (AHI = 5.5 ± 11.7 events/hour). Therefore, the AHI results of the PM showed a strong and positive correlation with those of the PSG (r = 0.70, p < 0.0001).
Conclusion The PM test can be a useful tool for OSA diagnosis in patients with COPD.
Publication History
Received: 10 April 2023
Accepted: 11 September 2023
Article published online:
29 May 2024
© 2024. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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