Can the Electronic Nose Smell COVID-19?

NCT04475562 | Completed

• 1 other identifier: eNoseCOVID
• Study Type: interventional
• Target: 219
• Locations: 1 country
• Sites: 1

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.

Conditions

SARS-CoV Infection; Covid19

Keywords

Electronic nose; Volatile organic compounds; Diagnosis

Outcome Measures

Primary Outcomes (1)

• 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

Study Arms (1)

COVID-19 suspected

OTHER

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

Interventions

Aeonose DEVICE

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.

COVID-19 suspected

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Participants of whom an oropharyngeal or nasopharyngeal swab was collected to perform RT-PCR on.

You may not qualify if:

• Participants who were experiencing dyspnea or needed supplemental oxygen.

Sponsors & Collaborators

• Maastricht University Medical Center: lead

Study Sites (1)

Maastricht University Medical Center

Maastricht, 6229 HX, Netherlands

Location

Related Publications (6)

• 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. No abstract available.

  PMID: 32091533 BACKGROUND

• 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.

  PMID: 24421258 BACKGROUND

• 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.

  PMID: 29909757 BACKGROUND

• Bikov A, Lazar 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.

  PMID: 26056127 BACKGROUND

• 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.

  PMID: 23956311 BACKGROUND

• 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.

  PMID: 27310311 BACKGROUND

MeSH Terms

Conditions

Severe Acute Respiratory Syndrome; COVID-19; Disease

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Virus Diseases; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Lung Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof. Dr. Nicole D. Bouvy

Study Record Dates

• First Submitted: July 15, 2020
• First Posted: July 17, 2020
• Study Start: April 6, 2020
• Primary Completion: May 6, 2020
• Study Completion: July 1, 2020
• Last Updated: July 17, 2020

Record last verified: 2020-07

Data Sharing

• IPD Sharing: Will share

Locations

NL (1)