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NCT04855539 Clinical Trial

Coronavirus: Ventilator Outcomes Using Artificial Intelligence Chest Radiographs & Other Evidence-based Co-variates

Covid19 Clinical Trial

— COVID VOICE  

Official title:
Coronavirus Infectious Disease 2019: Ventilator Outcomes Using Artificial Intelligence, Chest Radiographs and Other Evidence-based Co-variates (COVID VOICE)

Clinical Trial Details — Status: Recruiting

Administrative data
NCT number NCT04855539
Other study ID # IRAS 232823
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date March 1, 2020
Est. completion date December 1, 2021

Study information
Verified date September 2021
Source King's College Hospital NHS Trust
Contact Thomas C Booth, PhD
Phone +44203299482
Email thomas.booth@kcl.ac.uk
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.

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

Recruitment information / eligibility
Status Recruiting
Enrollment 300
Est. completion date December 1, 2021
Est. primary completion date May 1, 2021
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility 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

Study Design

Related Conditions & MeSH terms

Locations
Country Name City State
United Kingdom Guy's and St Thomas' Hospital London
United Kingdom King's College Hospital London
United Kingdom Princess Royal University Hospital Orpington Kent

Sponsors (2)
Lead Sponsor Collaborator
King's College Hospital NHS Trust King's College London

Country where clinical trial is conducted

United Kingdom, 

Outcome
Type Measure Description Time frame Safety issue
Primary Sensitivity and specificity of a convolutional neural network to predict survival outcome Defined by sensitivity, specificity, positive and negative predictive values 1 month
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