A new study will apply Artificial Intelligence (AI) technology to look for predictive patterns in the vital signs of COVID-19 patients that could alert the medical team about any deterioration.
The Manchester-based trial is sponsored by The Christie NHS Foundation Trust together with the Manchester University NHS Foundation Trust (MFT) with additional participation from Aptus Clinical and core AI capabilities provided by Zenzium, Ltd. (Cheshire, UK).
The COSMIC-19 (COntinious Signs Monitoring In Covid-19 patients) pilot study aims to recruit 60 inpatients on general wards who are suspected or confirmed to have COVID-19. Approximately 10-20% of hospital inpatients with COVID-19 will need intensive care. The patients on the trial will be monitored for 20 days until either placed on a ventilator or discharged from hospital.
The study will use wireless wearable sensors to automatically collect each patient’s vital signs together with clinical data and observations. Zenzium will then apply its AI technology to look for predictive patterns in the patients’ vital signs that could alert the medical team if the patient is deteriorating. If the prediction indicates that the patient needs critical care, the medical team can intervene earlier to give patients the best chance of recovery. Zenzium’s core technology, including DeepHRV, is based on Deep Learning as applied to time-series measurements and data.
“We are extremely excited to apply our AI technology based on time-series Deep Learning including DeepHRV to this challenge with the potential to make a substantial impact on patient outcomes,” said Anthony D. Bashall, Managing Director & Founder of Zenzium.
“Unfortunately some patients who are suffering from COVID-19 on our hospital wards can become seriously unwell. By using this system, we hope to be able to identify these patients early and this may mean we can optimize their management without the need for them to go to intensive care,” said Professor Fiona Thistlethwaite, medical oncologist at The Christie, who will lead the trial.