Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/182995
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dc.contributor.authorFontes de Oliveira, Luciana-
dc.contributor.authorMallafré Muro, Celia-
dc.contributor.authorGiner, Jordi-
dc.contributor.authorPerea, Lídia-
dc.contributor.authorSibila Vidal, Oriol-
dc.contributor.authorPardo Martínez, Antonio-
dc.contributor.authorMarco Colás, Santiago-
dc.date.accessioned2022-02-07T16:23:38Z-
dc.date.available2022-02-07T16:23:38Z-
dc.date.issued2022-02-01-
dc.identifier.issn0009-8981-
dc.identifier.urihttps://hdl.handle.net/2445/182995-
dc.description.abstractBackground 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% (CI95%: 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.-
dc.format.extent8 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1016/j.cca.2021.12.019-
dc.relation.ispartofClinica Chimica Acta, 2022, vol. 526, p. 6-13-
dc.relation.urihttps://doi.org/10.1016/j.cca.2021.12.019-
dc.rightscc-by-nc-nd (c) Fontes de Oliveira, Luciana, 2022-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.sourceArticles publicats en revistes (Enginyeria Electrònica i Biomèdica)-
dc.subject.classificationMalalties bronquials-
dc.subject.classificationProves funcionals respiratòries-
dc.subject.otherBronchial diseases-
dc.subject.otherRespiratory function tests-
dc.titleBreath analysis using electronic nose and gas chromatography-mass spectrometry: A pilot study on bronchial infections in bronchiectasis-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec717382-
dc.date.updated2022-02-07T16:23:39Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.pmid34953821-
Appears in Collections:Articles publicats en revistes (Enginyeria Electrònica i Biomèdica)
Articles publicats en revistes (Institut de Bioenginyeria de Catalunya (IBEC))

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