Computer algorithm could aid in early detection of life-threatening sepsis
For a patient with sepsis—which kills more Americans every year than AIDS and breast and prostate cancer combined—hours can make the difference between life and death.
The quest for early diagnosis of this life-threatening condition now takes a step forward, as Johns Hopkins University researchers report on a more effective way to spot hospital patients at risk of septic shock.
The new computer-based method correctly predicts septic shock in 85 percent of cases, without increasing the false positive rate from screening methods that are common now.
“But the critical advance our study makes is to detect these patients early enough that clinicians have time to intervene,” says Suchi Saria, an assistant professor of computer science and health policy at Johns Hopkins’ Whiting School of Engineering. She led the study, published today as the cover story in the journal Science Translational Medicine.
More than two-thirds of the time, the method was able to predict septic shock before any organ dysfunction. That is a 60 percent improvement over existing screening protocols.
Excerpted from The Hub. Read the complete story here.