COVID VOICE: Coronavirus: Ventilator Outcomes Using Artificial Intelligence Chest Radiographs & Other Evidence-based Co-variates
Study Details
Study Description
Brief Summary
We will determine ventilator outcomes to Coronavirus Infectious Disease 2019 (COVID-19) using artificial Intelligence with inputs of chest radiographs and other evidence-based co-variates.
Detailed Description
The chest radiograph (chest x-ray) has emerged as the United Kingdom's National Health Service (NHS) frontline diagnostic imaging test for COVID-19, in conjunction with clinical history and key blood markers: C-reactive protein (CRP) and lymphopenia. Typically, every suspected COVID-19 patient presenting to the emergency department is undergoing blood tests and a chest radiograph. Therefore, it has become critical for radiologists to review and "hot" report the chest x-ray urgently.
Primary Objective: Use chest radiographs and clinical data to determine whether patient can survive with a ventilator
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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wave 1
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wave 2
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Outcome Measures
Primary Outcome Measures
- Sensitivity and specificity of a convolutional neural network to predict survival outcome [1 month]
Defined by sensitivity, specificity, positive and negative predictive values
Eligibility Criteria
Criteria
Inclusion Criteria:
Admitted to intensive care unit (ITU) or equivalent COVID-19 polymerase chain reaction (PCR) positive
Exclusion Criteria:
No imaging prior to ITU admission
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
---|---|---|---|---|---|
1 | Princess Royal University Hospital | Orpington | Kent | United Kingdom | |
2 | Guy's and St Thomas' Hospital | London | United Kingdom | ||
3 | King's College Hospital | London | United Kingdom |
Sponsors and Collaborators
- King's College Hospital NHS Trust
- King's College London
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- IRAS 232823