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Purpose: The analysis of breath-print, has been proposed as an attractive alternative to investigate possible biomarkers of Chronic Obstructive Pulmonary Disease (COPD). The aim of the present study was to discriminate between healthy subjects, patients with COPD associated with smoking (COPD-S) and patients with COPD associated with household air pollution (COPD-HAP). Methods: A cross-sectional study of 294 participants was conducted, 88 with smoking associated COPD, 28 associated with HAP and 178 healthy subjects. Breath-print analysis was performed by using the Cyranose 320 electronic nose. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA) and Support Vector Machine (SVM) and the test's diagnostic power by means of ROC (Receiver Operating Characteristic) curves. Results: The results indicated that the breath-print of patients with COPD is different from the one of healthy subjects explaining a variability of 93.8%25 with a correct prediction of 97.8%25 and correct classification of 100%25,also positive and negative predictive value of 96.5 and 100%25 respectively. Furthermore, the breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference. Conclusions: The breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference, which demonstrates that the breath-print is related to the disease and not to causality. With these results, the analysis of the breath-print of COPD is proposed as an alternative for a screening method in future clinical applications. © 2020 Elsevier Ltd
Identification of breath-prints for the COPD detection associated with smoking and household air pollution by electronic nose
Purpose: The analysis of breath-print, has been proposed as an attractive alternative to investigate possible biomarkers of Chronic Obstructive Pulmonary Disease (COPD). The aim of the present study was to discriminate between healthy subjects, patients with COPD associated with smoking (COPD-S) and patients with COPD associated with household air pollution (COPD-HAP). Methods: A cross-sectional study of 294 participants was conducted, 88 with smoking associated COPD, 28 associated with HAP and 178 healthy subjects. Breath-print analysis was performed by using the Cyranose 320 electronic nose. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA) and Support Vector Machine (SVM) and the test%27s diagnostic power by means of ROC (Receiver Operating Characteristic) curves. Results: The results indicated that the breath-print of patients with COPD is different from the one of healthy subjects explaining a variability of 93.8%25 with a correct prediction of 97.8%25 and correct classification of 100%25,also positive and negative predictive value of 96.5 and 100%25 respectively. Furthermore, the breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference. Conclusions: The breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference, which demonstrates that the breath-print is related to the disease and not to causality. With these results, the analysis of the breath-print of COPD is proposed as an alternative for a screening method in future clinical applications. © 2020 Elsevier Ltd
Burning biomass fuel; COPD; Electronic nose; Exhaled breath; Smoking salbutamol; aged; Article; breath analysis; breath print analysis; case control study; chronic obstructive lung disease; controlled study; cross-sectional study; diagnostic accuracy; diagnostic test accuracy study; discriminant analysis; disease classification; female; forced expiratory volume; forced vital capacity; household; human; indoor air pollution; major clinical study; male; prediction; predictive value; principal component analysis; priority journal; screening; smoking; spirometry; support vector machine; adverse event; breath analysis; chronic obstructive lung disease; diagnostic imaging; electronic nose; family size; indoor air pollution; middle aged; procedures; receiver operating characteristic; smoking; very elderly; Aged; Aged, 80 and over; Air Pollution, Indoor; Breath Tests; Cross-Sectional Studies; Electronic Nose; Family Characteristics; Female; Humans; Male; Middle Aged; Pulmonary Disease, Chronic Obstructive; ROC Curve; Smoking
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