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Grant: Operating Grant: COVID-19 Rapid Research Funding Opportunity - Diagnostics

University of British Columbia

$260,326.00

Point of Care Heart-Lung Imaging for Patients Presenting with COVID-19 Symptoms: Artificial Intelligence Precision Modeling for Prediction of Outcomes

FY 2020-21

Summary
The global COVID-19 pandemic has placed a huge burden on health care systems and upended our way of life. It is caused by the highly infectious virus, SARS-CoV-2. Rapid and accurate testing for viral infection is needed to prevent spread of disease in hospitals and the community so that infected people can be identified early and treated effectively. EARLY COVID-19 symptoms are similar to many other respiratory viruses, like the flu and common cold, making it hard to identify in sick patients.The current approach to SARS-CoV-2 testing can be inaccurate and slow to return results. Improving diagnosis of COVID-19 will be even more important as flu season approaches. Our experience to date in treating patients with COVID-19 symptoms has shown that ultrasound imaging of the heart and lung may help identify positive cases earlier. Ultrasound is fast and safe. It can be performed at the bedside [point of care ultrasound (POCUS)] when patients first enter the hospital, by any physician with remote support from POCUS experts. In this study, we will test if adding heart and lung ultrasound images to existing clinical and laboratory tests can improve the accuracy and speed of COVID-19 diagnosis. A total of 16 hospitals across British Columbia and Ontario will participate in this study, and we will analyze this large data set using artificial intelligence (AI). Our team has already developed a platform to share ultrasound data and applied AI to study other heart diseases, so we are ready to rapidly apply this approach to COVID-19. If POCUS is effective it would allow earlier treatment and isolation of positive cases, reducing exposure of frontline health care workers and the public to the virus, improving both patient care and the distribution of health resources like personal protective equipment, intensive care beds and ventilators. Because POCUS-based COVID-19 diagnosis can be performed remotely it could also be applied in long term care facilities and in rural areas.
Program
Operating Grant: COVID-19 Rapid Research Funding Opportunity - Diagnostics
Location
British Columbia, Canada
Recipient Type
Academia
Type
Grant
Source
CIHR Funding Decisions Database

As published

Id
429336
Name
Tsang Teresa S
Region
British Columbia
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Circulatory and Respiratory Health
Theme2
Clinical
Prcname2
COVID-19 Rapid Research - Diagnostics
Projecttitle
Point of Care Heart-Lung Imaging for Patients Presenting with COVID-19 Symptoms: Artificial Intelligence Precision Modeling for Prediction of Outcomes
Programtype2
Operating Grants
Orgnameinp2
University of British Columbia
Cihramount2
$260,326
Cihrequipment2
$0
Programname2
Operating Grant: COVID-19 Rapid Research Funding Opportunity - Diagnostics
Keyworddelim
Artificial Intelligence; Cardiac Imaging; Covid-19; Lung Imaging; Point-Of-Care Ultrasound
Abstract
The global COVID-19 pandemic has placed a huge burden on health care systems and upended our way of life. It is caused by the highly infectious virus, SARS-CoV-2. Rapid and accurate testing for viral infection is needed to prevent spread of disease in hospitals and the community so that infected people can be identified early and treated effectively. EARLY COVID-19 symptoms are similar to many other respiratory viruses, like the flu and common cold, making it hard to identify in sick patients.The current approach to SARS-CoV-2 testing can be inaccurate and slow to return results. Improving diagnosis of COVID-19 will be even more important as flu season approaches. Our experience to date in treating patients with COVID-19 symptoms has shown that ultrasound imaging of the heart and lung may help identify positive cases earlier. Ultrasound is fast and safe. It can be performed at the bedside [point of care ultrasound (POCUS)] when patients first enter the hospital, by any physician with remote support from POCUS experts. In this study, we will test if adding heart and lung ultrasound images to existing clinical and laboratory tests can improve the accuracy and speed of COVID-19 diagnosis. A total of 16 hospitals across British Columbia and Ontario will participate in this study, and we will analyze this large data set using artificial intelligence (AI). Our team has already developed a platform to share ultrasound data and applied AI to study other heart diseases, so we are ready to rapidly apply this approach to COVID-19. If POCUS is effective it would allow earlier treatment and isolation of positive cases, reducing exposure of frontline health care workers and the public to the virus, improving both patient care and the distribution of health resources like personal protective equipment, intensive care beds and ventilators. Because POCUS-based COVID-19 diagnosis can be performed remotely it could also be applied in long term care facilities and in rural areas.
Competitiondate
202005
Approvedterm2
1 yr 0 mth
Pinamesdelim
Tsang, Teresa S; Abolmaesumi, Purang; McGrail, Kimberlyn M
Approvedterm
1 an 0 mois
Cihrcontribution2
~ $260,326~ $0~