Researchers have developed a new computer-aided model to identify early symptoms of sepsis -- a potentially life-threatening condition caused by the body's response to an infection.

Sepsis is a major cause of death in hospitals, and early detection is key to preventing deaths. Every hour of delay is linked to a 7 per cent reduction of survival. The study showed that the computer-aided National Early Warning Score (cNEWS) determined if it could enhance the accuracy of predicting sepsis. The score can trigger screening for sepsis within 30 minutes.

"The main advantage of these computer models is that they are designed to incorporate data that exist in the patient record, can be easily automated and place no extra burden on the hospital staff to collect additional information," said Mohammed A. Mohammed, Professor at the University of Bradford in Britain.

"These risk scores should support, rather than replace, clinical judgment. We hope they will heighten awareness of sepsis with additional information on this serious condition," he added, in the paper published in Canadian Medical Association Journal. cNEWS will now be introduced carefully into hospitals with appropriate information technology infrastructure, the study noted.