1. Identification of recent exacerbations in COPD patients by electronic nose
- Author
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Eric G. Haarman, Annelies Lucas, Paul Brinkman, Job J.M.H. van Bragt, Els J.M. Weersink, Sigrid Kester, Elisabeth H. Bel, Frans H.C. de Jongh, Johannes C C M In 't Veen, Rianne de Vries, Susanne J. H. Vijverberg, Anke H. Maitland-van der Zee, Peter J. Sterk, Graduate School, APH - Personalized Medicine, Amsterdam Reproduction & Development (AR&D), Pulmonology, Paediatric Pulmonology, Pulmonary Medicine, Pediatric surgery, and Pulmonary medicine
- Subjects
Pulmonary and Respiratory Medicine ,0303 health sciences ,medicine.medical_specialty ,COPD ,Receiver operating characteristic ,Exacerbation ,Electronic nose ,business.industry ,Copd patients ,lcsh:R ,lcsh:Medicine ,Original Articles ,medicine.disease ,Linear discriminant analysis ,03 medical and health sciences ,0302 clinical medicine ,030228 respiratory system ,Breath gas analysis ,Internal medicine ,Cohort ,medicine ,business ,030304 developmental biology - Abstract
Molecular profiling of exhaled breath by electronic nose (eNose) might be suitable as a noninvasive tool that can help in monitoring of clinically unstable COPD patients. However, supporting data are still lacking. Therefore, as a first step, this study aimed to determine the accuracy of exhaled breath analysis by eNose to identify COPD patients who recently exacerbated, defined as an exacerbation in the previous 3 months. Data for this exploratory, cross-sectional study were extracted from the multicentre BreathCloud cohort. Patients with a physician-reported diagnosis of COPD (n=364) on maintenance treatment were included in the analysis. Exacerbations were defined as a worsening of respiratory symptoms requiring treatment with oral corticosteroids, antibiotics or both. Data analysis involved eNose signal processing, ambient air correction and statistics based on principal component (PC) analysis followed by linear discriminant analysis (LDA). Before analysis, patients were randomly divided into a training (n=254) and validation (n=110) set. In the training set, LDA based on PCs 1–4 discriminated between patients with a recent exacerbation or no exacerbation with high accuracy (receiver operating characteristic (ROC)–area under the curve (AUC)=0.98, 95% CI 0.97–1.00). This high accuracy was confirmed in the validation set (AUC=0.98, 95% CI 0.94–1.00). Smoking, health status score, use of inhaled corticosteroids or vital capacity did not influence these results. Exhaled breath analysis by eNose can discriminate with high accuracy between COPD patients who experienced an exacerbation within 3 months prior to measurement and those who did not. This suggests that COPD patients who recently exacerbated have their own exhaled molecular fingerprint that could be valuable for monitoring purposes., Exhaled breath analysis by eNose can identify COPD patients who recently exacerbated with high accuracy. This suggests that these patients have their own exhaled molecular fingerprint that could be valuable for monitoring purposes. https://bit.ly/34vTyrH
- Published
- 2020