search
Back to results

Can the Electronic Nose Smell COVID-19?

Primary Purpose

SARS-CoV Infection, Covid19

Status
Completed
Phase
Not Applicable
Locations
Netherlands
Study Type
Interventional
Intervention
Aeonose
Sponsored by
Maastricht University Medical Center
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for SARS-CoV Infection focused on measuring Electronic nose, Volatile organic compounds, Diagnosis

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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.

Sites / Locations

  • Maastricht University Medical Center

Arms of the Study

Arm 1

Arm Type

Other

Arm Label

COVID-19 suspected

Arm Description

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.

Outcomes

Primary Outcome Measures

COVID 19 positive vs negative
Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.

Secondary Outcome Measures

Full Information

First Posted
July 15, 2020
Last Updated
July 16, 2020
Sponsor
Maastricht University Medical Center
search

1. Study Identification

Unique Protocol Identification Number
NCT04475562
Brief Title
Can the Electronic Nose Smell COVID-19?
Official Title
Can the Electronic Nose Smell COVID-19? A Proof-of-principle Study
Study Type
Interventional

2. Study Status

Record Verification Date
July 2020
Overall Recruitment Status
Completed
Study Start Date
April 6, 2020 (Actual)
Primary Completion Date
May 6, 2020 (Actual)
Study Completion Date
July 1, 2020 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Maastricht University Medical Center

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No

5. 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
SARS-CoV Infection, Covid19
Keywords
Electronic nose, Volatile organic compounds, Diagnosis

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
219 (Actual)

8. Arms, Groups, and Interventions

Arm Title
COVID-19 suspected
Arm Type
Other
Arm Description
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.
Intervention Type
Device
Intervention Name(s)
Aeonose
Intervention Description
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.
Primary Outcome Measure Information:
Title
COVID 19 positive vs negative
Description
Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.
Time Frame
3 months

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility 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.
Facility Information:
Facility Name
Maastricht University Medical Center
City
Maastricht
ZIP/Postal Code
6229 HX
Country
Netherlands

12. IPD Sharing Statement

Plan to Share IPD
Yes
Citations:
PubMed Identifier
32091533
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 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648. No abstract available.
Results Reference
background
PubMed Identifier
24421258
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.
Results Reference
background
PubMed Identifier
29909757
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.
Results Reference
background
PubMed Identifier
26056127
Citation
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.
Results Reference
background
PubMed Identifier
23956311
Citation
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.
Results Reference
background
PubMed Identifier
27310311
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.
Results Reference
background

Learn more about this trial

Can the Electronic Nose Smell COVID-19?

We'll reach out to this number within 24 hrs