The analysis of volatile organic compounds (VOCs) by an electronic nose (e-nose) is a groundbreaking method that provides distinct exhaled molecular patterns in several respiratory and systemic diseases. It has been shown that an e-nose can detect obstructive sleep apnea (OSA) as well as chronic obstructive pulmonary disease (COPD). OSA and COPD are sometimes associated into the so-called overlap syndrome (OVS). In this pilot study we hypothesized that an e-nose could discriminate the exhaled breath of patients with OVS from that of subjects with OSA and COPD alone. Thirteen patients with OSA, 15 patients with COPD and 13 with OVS participated in a cross-sectional study. Exhaled breath was collected by a formerly validated method and sampled by using an electronic nose (Cyranose 320). Raw data were analyzed by canonical discriminant analysis on principal component reduction. Cross-validation accuracy (CVA) and ROC-curves were calculated. External validation in newly recruited patients (6 OSA, 6 OVS and 6 COPD) was tested using the previous training set. Breathprints of patients with OSA clustered distinctly from those with OVS (CVA = 96.2%) as well as those with COPD (CVA = 82.1%). Breathprints from OVS were not significantly separated from those of COPD (CVA = 67.9%). External validation confirmed the above findings. The e-nose can distinguish with high accuracy the exhaled VOC-profile of patients with OSA from those with OVS as well as those with COPD. This warrants future studies to confirm the potential of this technique in the non-invasive detection of sleep apnea.

Exhaled breath profiling in patients with COPD and OSA overlap syndrome: A pilot study

DRAGONIERI, SILVANO;QUARANTA, VITALIANO NICOLA;CARRATU', Pierluigi;RESTA, Onofrio
2016

Abstract

The analysis of volatile organic compounds (VOCs) by an electronic nose (e-nose) is a groundbreaking method that provides distinct exhaled molecular patterns in several respiratory and systemic diseases. It has been shown that an e-nose can detect obstructive sleep apnea (OSA) as well as chronic obstructive pulmonary disease (COPD). OSA and COPD are sometimes associated into the so-called overlap syndrome (OVS). In this pilot study we hypothesized that an e-nose could discriminate the exhaled breath of patients with OVS from that of subjects with OSA and COPD alone. Thirteen patients with OSA, 15 patients with COPD and 13 with OVS participated in a cross-sectional study. Exhaled breath was collected by a formerly validated method and sampled by using an electronic nose (Cyranose 320). Raw data were analyzed by canonical discriminant analysis on principal component reduction. Cross-validation accuracy (CVA) and ROC-curves were calculated. External validation in newly recruited patients (6 OSA, 6 OVS and 6 COPD) was tested using the previous training set. Breathprints of patients with OSA clustered distinctly from those with OVS (CVA = 96.2%) as well as those with COPD (CVA = 82.1%). Breathprints from OVS were not significantly separated from those of COPD (CVA = 67.9%). External validation confirmed the above findings. The e-nose can distinguish with high accuracy the exhaled VOC-profile of patients with OSA from those with OVS as well as those with COPD. This warrants future studies to confirm the potential of this technique in the non-invasive detection of sleep apnea.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/191367
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