Breath analysis using electronic nose and gas chromatography-mass spectrometry : A pilot study on bronchial infections in bronchiectasis
Fontes de Oliveira, Luciana (Institute for Bioengineering of Catalonia (IBEC). The Barcelona Institute of Science and Technology. Signal and Information Processing for Sensing Systems)
Mallafré-Muro, Celia (Universitat de Barcelona. Departament d'Enginyeria Electrònica i Biomèdica)
Giner, Jordi (Institut d'Investigació Biomèdica Sant Pau)
Perea, Lidia (Institut d'Investigacions Biomèdiques August Pi i Sunyer)
Sibila, Oriol (Institut d'Investigacions Biomèdiques August Pi i Sunyer)
Pardo, Antonio (Universitat de Barcelona. Departament d'Enginyeria Electrònica i Biomèdica)
Marco, Santiago (Universitat de Barcelona. Departament d'Enginyeria Electrònica i Biomèdica)

Date:	2022
Abstract:	Background and aims: In this work, breath samples from clinically stable bronchiectasis patients with and without bronchial infections by Pseudomonas Aeruginosa- PA) were collected and chemically analysed to determine if they have clinical value in the monitoring of these patients. Materials and methods: A cohort was recruited inviting bronchiectasis patients (25) and controls (9). Among the former group, 12 members were suffering PA infection. Breath samples were collected in Tedlar bags and analyzed by e-nose and Gas Chromatography-Mass Spectrometry (GC-MS). The obtained data were analyzed by chemometric methods to determine their discriminant power in regards to their health condition. Results were evaluated with blind samples. Results: Breath analysis by electronic nose successfully separated the three groups with an overall classification rate of 84% for the three-class classification problem. The best discrimination was obtained between control and bronchiectasis with PA infection samples 100% (CI: 84-100%) on external validation and the results were confirmed by permutation tests. The discrimination analysis by GC-MS provided good results but did not reach proper statistical significance after a permutation test. Conclusions: Breath sample analysis by electronic nose followed by proper predictive models successfully differentiated between control, Bronchiectasis and Bronchiectasis PA samples.
Grants:	European Commission. Horizon 2020 712754 Ministerio de Economía y Competitividad SEV-2014-0425 Ministerio de Economía y Competitividad RTI2018-098577-B-C22 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017SGR1721 Instituto de Salud Carlos III PI18/00311
Note:	Altres ajuts: Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya; the European Social Fund (ESF); Institut de Bioenginyeria de Catalunya (IBEC); Sociedad Española de Neumología y Cirugía Torácica (SEPAR); Societat Catalana de Pneumologia (SOCAP); Fundació Catalana de Pneumologia (FUCAP).
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Breath analysis ; Bronchiectasis ; Signal processing ; E-nose ; GC-MS
Published in:	Clinica Chimica Acta, Vol. 526 (january 2022) , p. 6-13, ISSN 1873-3492

DOI: 10.1016/j.cca.2021.12.019
PMID: 34953821

8 p, 1.1 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut de Recerca Sant Pau
Articles > Research articles
Articles > Published articles