Can the Electronic Nose Smell COVID-19?
Study Details
Study Description
Brief Summary
Infection with SARS-CoV-2 causes Corona Virus Disease (COVID-19). The most standard diagnostic method is reverse transcription-polymerase chain reaction (RT-PCR) on a nasopharyngeal and/or an oropharyngeal swab. The high occurrence of false-negative results due to the non-presence of SARS-CoV-2 in the oropharyngeal environment renders this sampling method not ideal. Therefore, a new sampling device is desirable. This proof-of-principle study investigates the possibility to train machine-learning classifiers with an electronic nose (Aeonose) to differentiate between COVID-19 positive- and negative persons based on volatile organic compounds (VOCs) analysis.
Methods: between April and June 2020, participants were invited for breath analysis when a swab for RT-PCR was collected. If the RT-PCR resulted negative, presence of SARS-CoV-2 specific antibodies was checked to confirm the negative result. All participants breathed through the Aeonose for five minutes. This device contains metal-oxide sensors that change in conductivity upon reaction with VOCs in exhaled breath. These conductivity changes are input data for machine-learning and used for pattern recognition. The result is a value between -1 and +1, indicating the infection probability.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Other: COVID-19 suspected Participants were recruited at the outpatient clinic for MUMC+ employees with COVID-19 symptoms or at the nursing unit where a SARS-CoV-2 patient was admitted. |
Device: Aeonose
All participants breathed through the Aeonose for five minutes. This device contains metal-oxide sensors that change in conductivity upon reaction with VOCs in exhaled breath. These conductivity changes are input data for machine-learning and used for pattern recognition. A nose clip was placed on the nose of each participant to avoid entry of non-filtered air in the device. Before measuring, the Aeonose was flushed with room air, guided through a carbon filter as well. During each measurement, a video was displayed to distract the participant and to reduce the chance of hyperventilation. Failed breath tests were excluded from analysis; the reason for failure was documented. Four similar Aeonose devices were used for breath analysis. A full-measurement procedure required sixteen minutes.
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Outcome Measures
Primary Outcome Measures
- COVID 19 positive vs negative [3 months]
Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.
Eligibility Criteria
Criteria
Inclusion Criteria:
- Participants of whom an oropharyngeal or nasopharyngeal swab was collected to perform RT-PCR on.
Exclusion Criteria:
- Participants who were experiencing dyspnea or needed supplemental oxygen.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Maastricht University Medical Center | Maastricht | Netherlands | 6229 HX |
Sponsors and Collaborators
- Maastricht University Medical Center
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
- Bijland LR, Bomers MK, Smulders YM. Smelling the diagnosis: a review on the use of scent in diagnosing disease. Neth J Med. 2013 Jul-Aug;71(6):300-7. Review.
- Bikov A, Lázár Z, Horvath I. Established methodological issues in electronic nose research: how far are we from using these instruments in clinical settings of breath analysis? J Breath Res. 2015 Jun 9;9(3):034001. doi: 10.1088/1752-7155/9/3/034001. Review.
- de Lacy Costello B, Amann A, Al-Kateb H, Flynn C, Filipiak W, Khalid T, Osborne D, Ratcliffe NM. A review of the volatiles from the healthy human body. J Breath Res. 2014 Mar;8(1):014001. doi: 10.1088/1752-7155/8/1/014001. Epub 2014 Jan 13. Review.
- Schuermans VNE, Li Z, Jongen ACHM, Wu Z, Shi J, Ji J, Bouvy ND. Pilot Study: Detection of Gastric Cancer From Exhaled Air Analyzed With an Electronic Nose in Chinese Patients. Surg Innov. 2018 Oct;25(5):429-434. doi: 10.1177/1553350618781267. Epub 2018 Jun 18.
- van Geffen WH, Bruins M, Kerstjens HA. Diagnosing viral and bacterial respiratory infections in acute COPD exacerbations by an electronic nose: a pilot study. J Breath Res. 2016 Jun 16;10(3):036001. doi: 10.1088/1752-7155/10/3/036001.
- Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648.
- eNoseCOVID