Rapid COVID-19 AI Test Predicts Well against PCR Swab Results

A screening test conducted on patients arriving at the Emergency departments of the John Radcliffe Hospital in Oxford and the Horton General Hospital in Banbury has been found to accurately predict the COVID-19 status of 92.3% of patients within the first hour of coming to hospital.  Using data from clinical information routinely available (blood tests and vital signs),  the two-week CURIAL study(1) found  the Artificial Intelligence test correctly ruled-out COVID-19 97.6% of the time when compared against results of PCR laboratory swab testing, which typically takes 24 hours.

An infectious disease research team led by Dr Andrew Soltan, an NIHR Academic Clinical Fellow (Cardiology) at the John Radcliffe Hospital, joined fellow experts at the AI for Healthcare lab of Professor David Clifton, within Oxford’s Institute of Biomedical Engineering and also Professor David Eyre of the Oxford Big Data Institute to develop the test which was initiated in March. 

Dr Soltan, also a researcher at Oxford University’s Radcliffe Department of Medicine, said: ‘Every day around 350 people come to our Emergency Departments in the John Radcliffe Hospital in Oxford and the Horton General Hospital in Banbury, yet only a small number will be ill with COVID-19. The CURIAL AI test offers clinical teams the potential to rapidly and confidently rule-out a diagnosis of COVID-19 for a large majority of the patients who do not have the infection, while identifying patients at higher risk of testing positive. The higher-risk patients can then be cared for in clinical areas with additional infection-control precautions while swab test results are awaited.’

‘The turnaround time for COVID-19 swabs has come down since the start of the pandemic. However, until we have confirmation that patients are negative we must take additional precautions for patients with coronavirus symptoms, which are very common as we head in to winter. Patients screened by the AI test as low-risk could benefit from reduced delays to their care if we know sooner that they do not have COVID-19. A strength of our AI test is that it fits within the existing clinical care pathway and works with existing lab equipment. This means scaling it up will be relatively fast and cheap,’ he added.

Dr Ravi Pattanshetty, an A&E Consultant at the John Radcliffe Hospital supporting translation of the CURIAL into Emergency Departments, said: ‘The John Radcliffe Emergency Department will be conducting prospective validation of this AI tool in the coming months. We will be mainly using it to triage patients at the front door to help the flow of patients into various designated areas. We are very excited at the prospect of being able to use a tool which, should it prove successful, will help hospitals make more informed and rapid decisions with regards to patient flow. It has the potential to be tailored to be used in various scenarios.’

The researchers have now received an award from the University Medical and Life Sciences Translational Fund, comprising devolved funding from the Medical Research Council and Wellcome Trust and are working with Infectious Diseases and Emergency Department teams at the John Radcliffe Hospital to trial the CURIAL AI test in the clinical pathway. A collaboration with University Hospitals Birmingham will allow the team to validate the AI test’s performance using data from a different NHS organisation.

The team are also validating a version of the CURIAL AI test that uses near-patient blood tests that can be performed in 10 minutes, reducing the time the AI needs to exclude coronavirus infection from one hour to only minutes. A trial to evaluate the near-patient AI screening model, named CURIAL-Rapide, is expected to begin shortly at the John Radcliffe Hospital in Oxford.

David Clifton, Professor of Clinical Machine Learning at the Department of Engineering Science, said: ‘With many of our clinical colleagues working on the front lines to fight COVID-19, data scientists in Healthcare AI have a supporting role to play by constructing tools to help care for patients. The unique ecosystem at Oxford between hospitals and clinical AI teams gives us a great opportunity to contribute to the international effort against COVID-19. 

‘This project is a great example of what can be done, and at very great pace, to fast-track the development of technologies to help in the current pandemic – and to increase the resilience of the country’s healthcare system for any future events.

Published in the The Lancet Digital Health, Dec 11.