Sepsis Prevention in Surgery
Research type
Research Study
Full title
Sepsis Prevention in Surgery: Informing the Clinical Process through Artificial Intelligence
IRAS ID
280077
Contact name
Sarah Slight
Contact email
Sponsor organisation
Newcastle Univerity
Duration of Study in the UK
1 years, 11 months, 29 days
Research summary
Microbes, such as bacteria, viruses, fungi, can cause a life-threatening infectious condition known as sepsis. In Europe, mortality due to sepsis is estimated to be 38%.
Sepsis is a rapidly progressive condition, with patients deteriorating within a few hours and needing intensive treatment. Due to the increasingly resistant nature of bacterial strains causing sepsis, empirical antibiotic therapy may be unsuccessful in a significant proportion of patients presenting with this condition.
Protecting individuals from infections is the best solution to reduce the incidence of sepsis and associated mortality. This is especially important for individuals with underlying risk factors for infection. Like predicting weather and routes, diseases may be predicted with the use of artificial intelligence. Through these advanced technologies, it is possible to predict sepsis before it actually occurs based on an individual's risk factors. These algorithms can guide clinicians’ decision-making and thereby help protect patients from getting sepsis.
This project will involve the development of an artificial intelligence tool that can guide clinicians in predicting the likelihood of infection and subsequent sepsis in patients undergoing elective surgery. This tool will be prepared using non-identifiable data from patient records in Newcastle Upon Tyne Hospitals NHS Foundation Trust (NUTH).REC name
East Midlands - Leicester Central Research Ethics Committee
REC reference
20/EM/0183
Date of REC Opinion
3 Aug 2020
REC opinion
Further Information Favourable Opinion