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CompletedNCT04329507Updated Sep 8, 2021

Non-invasive Detection of Pneumonia in Context of Covid-19 Using Gas Chromatography - Ion Mobility Spectrometry (GC-IMS)

An observational study in COVID-19 and Respiratory Disease, sponsored by NHS Lothian. Completed at 1 site in United Kingdom. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2021-09-08.

Sponsored by NHS Lothian · Observational

Study type
Observational
Model
Case-control
Time perspective
Prospective
Enrollment
225
Ages
18 Years and older
Sex
All
01

Study summary

On Dec 31, 2019, a number of viral pneumonia cases were reported in China. The virus causing pneumonia was then identified as a new coronavirus called SARS-CoV-2. Since this time, the infection called coronavirus disease 2019 (COVID-19) has spread around the world, causing huge stress for health care systems. To diagnose this infection, throat and nose swabs are taken. Unfortunately, the results often take more than 24 hrs to return from a laboratory. Speeding diagnosis up would be of great help.

This study aims to look at the breath to find signs that might allow clinicians to diagnose the coronavirus infection at the bedside, without needing to send samples to the laboratory. To do this, the team will be using a machine called a BreathSpec which has been adapted to fit in the hospital for this purpose.

Read the detailed description

Analysis of volatile organic compounds (VOCs) in exhaled breath is of increasing interest in the diagnosis of lung infection. Over 2,000 VOCs can be detected through gas chromatography and mass spectrometry (GC-MS); patterns of VOC detected can offer information on chronic obstructive pulmonary disease, asthma, lung cancer and interstitial lung disease. Unfortunately, GC-MS while highly sensitive cannot be done at the bedside and at best takes hours to prepare samples, run the analysis and then interpret the results.

Compared with other methods of breath analysis, ion mobility spectrometry (IMS) offers a tenfold higher detection rate of VOCs. By coupling an ion mobility spectrometer with a GC column, GC-IMS offers immediate twofold separation of VOCs with visualisation in a three-dimensional chromatogram. The total analysis time is about 300 seconds and the equipment has been miniaturised to allow bedside analysis.

The BreathSpec machine has been previously used to study both radiation injury in patients undergoing radiotherapy at the Edinburgh Cancer Centre (REC ref 16-SS-0059, as part of the H2020 TOXI-triage project, http://www.toxi-triage.eu/) and pneumonia in patients presenting to the ED of the Royal Infirmary of Edinburgh (REC ref 18-LO-1029). This work has developed artificial intelligence methodology that allows rapid analysis of the vast amount of data collected from these breath samples to identify signatures that may indicate a particular pathological process such as pneumonia or radiation injury.

The TOXI-triage project showed that the BreathSpec GC-IMS could rapidly triage individuals to identify those who had been exposed to particular volatile liquids in a mass casualty situation (http://www.toxi-triage.eu/).

A pilot trial assessed chest infections at the Acute Medical Unit of the Royal Liverpool University Hospital. The final diagnostic model permitted fair discrimination between bacterial chest infections and chest infections due to other agents with an area under the receiver operator characteristic curve (AUC-ROC) of 0.73 (95% CI 0.61-0.86). The summary test characteristics were a sensitivity of 62% (95% CI 41-80%) and specificity of 80% (95% CI 64 - 91%) [8].

This was expanded in the EU H2020 funded "Breathspec Study" which aimed to differentiate breath samples from patients with bacterial or viral upper or lower respiratory tract infection. Over 1220 patients were recruited, with 191 patients identified as definitely bacterial infection and 671 classed as definitely not bacterial. Virology was undertaken on all patients, with 259 patients confirmed viral infection. Date processing is still on going to determine how well they can be distinguished using this methodology. More than 100 patients were recruited to this study in Edinburgh. Since then, artificial intelligence has been incorporated into our analytical processes, permitting faster and more refined analysis.

Our ambition is that this technology will identify a signature of Covid-19 pneumonia or within 10 min in non-invasively collected breath samples to allow triage of patients into high and low risk categories for Covid-19. This will allow targeting of scarce resources and complex protocols associated with high risk patients including personal protective equipment (PPE), cohorting, and dedicated medical and nursing personel.

A healthy volunteer arm was added in July 2020 - 40 particpants

02

Conditions studied

  • COVID-19
  • Respiratory Disease

Keywords

  • COVID-19
03

In context

COVID-19

7,640 studies on the registry are indexed under COVID-19; 488 are open to participants now.

This study's enrollment of 225 is below the median of 261 across 3,136 observational studies indexed under COVID-19.

Browse COVID-19 studies →

Lead sponsor

NHS Lothian is the lead sponsor of 51 studies on the registry; 6 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Sampling method
Non-probability sample

Study population

Patients presenting to hospital with respiratory signs and tested for SARS-CoV-2

Inclusion criteria

  • ≥18 years old with clinical features consistent with pneumonia or chest infection due to SARS-CoV-2 AND

    • presenting to the Royal Infirmary of Edinburgh where they are swabbed and triaged for Covid-19.

Exclusion criteria

Exclusion Criteria:

  • Inability to provide informed consent
  • Age 17 years or less
05

Study design

Observational model
Case-control
Time perspective
Prospective
Enrollment
225 participants (actual)
Patient registry
No

Interventions

  • Diagnostic testBreath test

    collection of an exhaled breath sample

06

What researchers measure

Primary outcomes

  1. To perform a study in patients with clinical features of pneumonia/chest infection to identify a signature of Covid-19 pneumonia in patients exposed to SARS-CoV-2, compared to unexposed patients or those without.

    breath sample collection

    Time frame: up to daily during hospital admission

Secondary outcomes

  1. Detection of markers of Covid-19 pneumonia in non-invasive breath samples.

    breath sample collection

    Time frame: multiple samples up to 60 days

  2. Relationship of this biomarker signature to the presence of SARS-CoV-2 in nasal and throat swabs.

    breath sample collection

    Time frame: multiple samples up to 60 days

  3. Subsequently, the signature's relationship to other biomarkers of SARS-CoV-2 infection which are currently being explored

    breath sample collection

    Time frame: multiple samples up to 60 days

  4. In a smaller group of participants, ideally daily non-invasive breath samples will be collected to determine if there are changes between SARS-CoV-2 positive patients and those that are negative until hospital discharge or undue participant burden .

    breath sample collection

    Time frame: multiple samples up to 60 days

07

Study locations

1 site
  • NHS Lothian
    Edinburgh, EH16 4SA, United Kingdom
08

References and documents

Individual participant data

Plan to share: Undecided — no plan made as yet - this research needs to be expedited during the pandemic

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 8, 2021, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT04329507
Lead sponsor
NHS Lothian
Responsible party
Sponsor
First posted
Apr 1, 2020
Start date
Mar 25, 2020
Primary completion
Jan 31, 2021
Completion
May 30, 2021
Last update
Sep 8, 2021

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Aug 2021. You cannot join it, but the record below documents what was studied.

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