Identification of recent exacerbations in COPD patients by electronic nose
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 bre...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
European Respiratory Society
2020-12-01
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| Series: | ERJ Open Research |
| Online Access: | http://openres.ersjournals.com/content/6/4/00307-2020.full |
| _version_ | 1818700508317089792 |
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| author | Job J.M.H. van Bragt Paul Brinkman Rianne de Vries Susanne J.H. Vijverberg Els J.M. Weersink Eric G. Haarman Frans H.C. de Jongh Sigrid Kester Annelies Lucas Johannes C.C.M. in 't Veen Peter J. Sterk Elisabeth H.D. Bel Anke H. Maitland-van der Zee |
| author_facet | Job J.M.H. van Bragt Paul Brinkman Rianne de Vries Susanne J.H. Vijverberg Els J.M. Weersink Eric G. Haarman Frans H.C. de Jongh Sigrid Kester Annelies Lucas Johannes C.C.M. in 't Veen Peter J. Sterk Elisabeth H.D. Bel Anke H. Maitland-van der Zee |
| author_sort | Job J.M.H. van Bragt |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T15:06:03Z |
| format | Article |
| id | doaj.art-c7ce607d47cb4c43b5ee15e6c9274687 |
| institution | Directory Open Access Journal |
| issn | 2312-0541 |
| language | English |
| last_indexed | 2024-12-17T15:06:03Z |
| publishDate | 2020-12-01 |
| publisher | European Respiratory Society |
| record_format | Article |
| series | ERJ Open Research |
| spelling | doaj.art-c7ce607d47cb4c43b5ee15e6c92746872022-12-21T21:43:47ZengEuropean Respiratory SocietyERJ Open Research2312-05412020-12-016410.1183/23120541.00307-202000307-2020Identification of recent exacerbations in COPD patients by electronic noseJob J.M.H. van Bragt0Paul Brinkman1Rianne de Vries2Susanne J.H. Vijverberg3Els J.M. Weersink4Eric G. Haarman5Frans H.C. de Jongh6Sigrid Kester7Annelies Lucas8Johannes C.C.M. in 't Veen9Peter J. Sterk10Elisabeth H.D. Bel11Anke H. Maitland-van der Zee12 Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, Vrije Universiteit Amsterdam, Dept of Pediatric Respiratory Medicine, Amsterdam, The Netherlands Medisch Spectrum Twente, Dept of Pulmonary Function, Enschede, The Netherlands Medisch Centrum Den Bosch Oost, ’s-Hertogenbosch, The Netherlands Diagnostiek voor U, Eindhoven, The Netherlands Franciscus Gasthuis and Vlietland/Erasmus MC, Dept of Pulmonology, Rotterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands Amsterdam UMC, University of Amsterdam, Dept of Respiratory Medicine, Amsterdam, The Netherlands 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.http://openres.ersjournals.com/content/6/4/00307-2020.full |
| spellingShingle | Job J.M.H. van Bragt Paul Brinkman Rianne de Vries Susanne J.H. Vijverberg Els J.M. Weersink Eric G. Haarman Frans H.C. de Jongh Sigrid Kester Annelies Lucas Johannes C.C.M. in 't Veen Peter J. Sterk Elisabeth H.D. Bel Anke H. Maitland-van der Zee Identification of recent exacerbations in COPD patients by electronic nose ERJ Open Research |
| title | Identification of recent exacerbations in COPD patients by electronic nose |
| title_full | Identification of recent exacerbations in COPD patients by electronic nose |
| title_fullStr | Identification of recent exacerbations in COPD patients by electronic nose |
| title_full_unstemmed | Identification of recent exacerbations in COPD patients by electronic nose |
| title_short | Identification of recent exacerbations in COPD patients by electronic nose |
| title_sort | identification of recent exacerbations in copd patients by electronic nose |
| url | http://openres.ersjournals.com/content/6/4/00307-2020.full |
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