2026-04-17T13:44:12Zhttps://recercat.cat/oai/request

oai:recercat.cat:2072/4713942025-07-29T22:13:53Zcom_2072_98col_2072_378192

00925njm 22002777a 4500 dc Fontes de Oliveira, Luciana author Mallafré-Muro, Celia author Giner, Jordi author Perea, Lidia author Sibila, Oriol author Pardo, Antonio author Marco, Santiago author 2022 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). 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. Breath analysis Bronchiectasis Signal processing E-nose GC-MS Breath analysis using electronic nose and gas chromatography-mass spectrometry : A pilot study on bronchial infections in bronchiectasis