Breath analysis using electronic nose and gas chromatography-mass spectrometry: A pilot study on bronchial infections in bronchiectasis


Por: Oliveira L.F.D., Mallafré-Muro C., Giner J., Perea L., Sibila O., Pardo A., Marco S.

Publicada: 1 ene 2022
Resumen:
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% (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. © 2021 The Author(s)

Filiaciones:
Oliveira L.F.D.:
 Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, Barcelona, 08028, Spain

Mallafré-Muro C.:
 Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, Barcelona, 08028, Spain

 Department of Electronics and Biomedical Engineering, University of Barcelona, Marti I Franqués 1, Barcelona, 08028, Spain

Giner J.:
 Department of Pneumology and Allergy, Hospital de la Sta. Creu I Sant Pau. Barcelona, Spain

Perea L.:
 Respiratory Department, Hospital Clinic, IDIBAPS, Barcelona, Spain

Sibila O.:
 Respiratory Department, Hospital Clinic, IDIBAPS, Barcelona, Spain

Pardo A.:
 Department of Electronics and Biomedical Engineering, University of Barcelona, Marti I Franqués 1, Barcelona, 08028, Spain

Marco S.:
 Signal and Information Processing for Sensing Systems, Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, Barcelona, 08028, Spain

 Department of Electronics and Biomedical Engineering, University of Barcelona, Marti I Franqués 1, Barcelona, 08028, Spain
ISSN: 00098981
Editorial
ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, Países Bajos
Tipo de documento: Article
Volumen: 526 Número:
Páginas: 6-13
WOS Id: 000799165800002
ID de PubMed: 34953821
imagen All Open Access, Hybrid Gold

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