Diagnostic performance of eNose technology in COVID-19 patients after hospitalization
Abstract Background Volatile organic compounds (VOCs) produced by human cells reflect metabolic and pathophysiological processes which can be detected with the use of electronic nose (eNose) technology. Analysis of exhaled breath may potentially play an important role in diagnosing COVID-19 and stra...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-04-01
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| Series: | BMC Pulmonary Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12890-023-02407-6 |
| _version_ | 1797841209942605824 |
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| author | B. F.M. van Raaij J. D. Veltman J. F. Hameete J. L. Stöger J. J.M. Geelhoed |
| author_facet | B. F.M. van Raaij J. D. Veltman J. F. Hameete J. L. Stöger J. J.M. Geelhoed |
| author_sort | B. F.M. van Raaij |
| collection | DOAJ |
| description | Abstract Background Volatile organic compounds (VOCs) produced by human cells reflect metabolic and pathophysiological processes which can be detected with the use of electronic nose (eNose) technology. Analysis of exhaled breath may potentially play an important role in diagnosing COVID-19 and stratification of patients based on pulmonary function or chest CT. Methods Breath profiles of COVID-19 patients were collected with an eNose device (SpiroNose) 3 months after discharge from the Leiden University Medical Centre and matched with breath profiles from healthy individuals for analysis. Principal component analysis was performed with leave-one-out cross validation and visualised with receiver operating characteristics. COVID-19 patients were stratified in subgroups with a normal pulmonary diffusion capacity versus patients with an impaired pulmonary diffusion capacity (DLCOc < 80% of predicted) and in subgroups with a normal chest CT versus patients with COVID-19 related chest CT abnormalities. Results The breath profiles of 135 COVID-19 patients were analysed and matched with 174 healthy controls. The SpiroNose differentiated between COVID-19 after hospitalization and healthy controls with an AUC of 0.893 (95-CI, 0.851–0.934). There was no difference in VOCs patterns in subgroups of COVID-19 patients based on diffusion capacity or chest CT. Conclusions COVID-19 patients have a breath profile distinguishable from healthy individuals shortly after hospitalization which can be detected using eNose technology. This may suggest ongoing inflammation or a common repair mechanism. The eNose could not differentiate between subgroups of COVID-19 patients based on pulmonary diffusion capacity or chest CT. |
| first_indexed | 2024-04-09T16:27:25Z |
| format | Article |
| id | doaj.art-59913f990f944d0dad7c3d8906f62def |
| institution | Directory Open Access Journal |
| issn | 1471-2466 |
| language | English |
| last_indexed | 2024-04-09T16:27:25Z |
| publishDate | 2023-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pulmonary Medicine |
| spelling | doaj.art-59913f990f944d0dad7c3d8906f62def2023-04-23T11:08:05ZengBMCBMC Pulmonary Medicine1471-24662023-04-012311710.1186/s12890-023-02407-6Diagnostic performance of eNose technology in COVID-19 patients after hospitalizationB. F.M. van Raaij0J. D. Veltman1J. F. Hameete2J. L. Stöger3J. J.M. Geelhoed4Department of Internal Medicine, Section of Geriatrics and Gerontology, Leiden University Medical CentreDepartment of Pulmonary Diseases, Amsterdam University Medical CentreDepartment of Pulmonary Diseases, Leiden University Medical CentreDepartment of Radiology, Leiden University Medical CentreDepartment of Pulmonary Diseases, Leiden University Medical CentreAbstract Background Volatile organic compounds (VOCs) produced by human cells reflect metabolic and pathophysiological processes which can be detected with the use of electronic nose (eNose) technology. Analysis of exhaled breath may potentially play an important role in diagnosing COVID-19 and stratification of patients based on pulmonary function or chest CT. Methods Breath profiles of COVID-19 patients were collected with an eNose device (SpiroNose) 3 months after discharge from the Leiden University Medical Centre and matched with breath profiles from healthy individuals for analysis. Principal component analysis was performed with leave-one-out cross validation and visualised with receiver operating characteristics. COVID-19 patients were stratified in subgroups with a normal pulmonary diffusion capacity versus patients with an impaired pulmonary diffusion capacity (DLCOc < 80% of predicted) and in subgroups with a normal chest CT versus patients with COVID-19 related chest CT abnormalities. Results The breath profiles of 135 COVID-19 patients were analysed and matched with 174 healthy controls. The SpiroNose differentiated between COVID-19 after hospitalization and healthy controls with an AUC of 0.893 (95-CI, 0.851–0.934). There was no difference in VOCs patterns in subgroups of COVID-19 patients based on diffusion capacity or chest CT. Conclusions COVID-19 patients have a breath profile distinguishable from healthy individuals shortly after hospitalization which can be detected using eNose technology. This may suggest ongoing inflammation or a common repair mechanism. The eNose could not differentiate between subgroups of COVID-19 patients based on pulmonary diffusion capacity or chest CT.https://doi.org/10.1186/s12890-023-02407-6Breath analysisCOVID-19Electronic nose technologyFollow-up |
| spellingShingle | B. F.M. van Raaij J. D. Veltman J. F. Hameete J. L. Stöger J. J.M. Geelhoed Diagnostic performance of eNose technology in COVID-19 patients after hospitalization BMC Pulmonary Medicine Breath analysis COVID-19 Electronic nose technology Follow-up |
| title | Diagnostic performance of eNose technology in COVID-19 patients after hospitalization |
| title_full | Diagnostic performance of eNose technology in COVID-19 patients after hospitalization |
| title_fullStr | Diagnostic performance of eNose technology in COVID-19 patients after hospitalization |
| title_full_unstemmed | Diagnostic performance of eNose technology in COVID-19 patients after hospitalization |
| title_short | Diagnostic performance of eNose technology in COVID-19 patients after hospitalization |
| title_sort | diagnostic performance of enose technology in covid 19 patients after hospitalization |
| topic | Breath analysis COVID-19 Electronic nose technology Follow-up |
| url | https://doi.org/10.1186/s12890-023-02407-6 |
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