Can the Electronic Nose Smell COVID-19?

Covid19 Clinical Trial

Official title:

Can the Electronic Nose Smell COVID-19? A Proof-of-principle Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04475562
• Other study ID #: eNoseCOVID
• Status: Completed
• Phase: N/A
• Start date: April 6, 2020
• Est. completion date: July 1, 2020

Study information

• Verified date: July 2020
• Source: Maastricht University Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 219
• Est. completion date: July 1, 2020
• Est. primary completion date: May 6, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Coronavirus Infections
• Covid19
• SARS-CoV Infection
• Severe Acute Respiratory Syndrome

Intervention

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.

Locations

Country	Name	City	State
Netherlands	Maastricht University Medical Center	Maastricht

Sponsors (1)

Lead Sponsor	Collaborator
Maastricht University Medical Center

Country where clinical trial is conducted

Netherlands, 

References & Publications (6)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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 Feb 24. doi: 10.1001/jama.2020.2648. [Epub ahead of print] — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	COVID 19 positive vs negative	Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.	3 months