Ignite Creation Date:
2024-05-06 @ 2:27 PM
Last Modification Date:
2024-10-26 @ 1:31 PM
Study NCT ID:
NCT04329507
Status:
COMPLETED
Last Update Posted:
2021-09-08
First Post:
2020-03-26
Brief Title:
Non-invasive Detection of Pneumonia in Context of Covid-19 Using Gas Chromatography - Ion Mobility Spectrometry GC-IMS
Sponsor:
NHS Lothian
Organization:
NHS Lothian
Study Overview
Official Title:
Non-invasive Detection of Pneumonia in Context of Covid-19 Using Gas Chromatography - Ion Mobility Spectrometry GC-IMS
Status:
COMPLETED
Status Verified Date:
2021-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief 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
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
Detailed Description:
Analysis of volatile organic compounds VOCs in exhaled breath is of increasing interest in the diagnosis of lung infection Over 2000 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 httpwwwtoxi-triageeu 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 httpwwwtoxi-triageeu
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 073 95 CI 061-086 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
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 httpwwwtoxi-triageeu 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 httpwwwtoxi-triageeu
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 073 95 CI 061-086 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None