AI-based early warning system for sepsis can improve patient outcomes

In a study by researchers at Case Western Reserve University and MetroHealth, emergency room patients flagged by an AI algorithm as potentially having sepsis received antibiotics sooner and had better outcomes than those receiving standard care for sepsis. The findings from the study have been published in the journal, Critical Care Medicine. Sepsis is a life-threatening reaction to an infection that occurs when the body's immune system overreacts to an infection and starts to damage the body's own tissues and organs. The prognosis of patients with sepsis is related to the severity or stage of sepsis, as well as to the underlying health status of the patient. It is estimated that patients with severe sepsis or septic shock have a mortality rate of about 40% to 60%, so it is very important that sepsis is detected as early as possible.