
Rapid bedside test predicts sepsis with over 90 percent accuracy
On May 27, 2025, Canadian scientists announced they have developed a blood test and portable device that can determine the onset of sepsis faster and more accurately than existing methods.Published today in Nature Communications, the test is more than 90 per cent accurate at identifying those at high risk of developing sepsis and represents a major milestone in the way doctors will evaluate and treat sepsis.
“Sepsis accounts for roughly 20 per cent of all global deaths,” said lead author Dr. Claudia dos Santos, a critical care physician and scientist at St. Michael’s Hospital. “Our test could be a powerful game changer, allowing physicians to quickly identify and treat patients before they begin to rapidly deteriorate.”
Sepsis is the body’s extreme reaction to an infection, causing the immune system to start attacking one’s own organs and tissues. It can lead to organ failure and death if not treated quickly. Predicting sepsis is difficult: early symptoms are non-specific, and current tests can take up to 18 hours and require specialized labs. This delay before treatment increases the chance of death by nearly eight per cent per hour.
Examining blood samples from more than 3,000 hospital patients with suspected sepsis, researchers from UBC and Sepset, a UBC spin-off biotechnology company, used machine learning to identify a six-gene expression signature “Sepset” that predicted sepsis nine times out of 10, and well before a formal diagnosis. With 248 additional blood samples using RT-PCR, (Reverse Transcription Polymerase Chain Reaction), a common hospital laboratory technique, the test was 94 per cent accurate in detecting early-stage sepsis in patients whose condition was about to worsen.
To bring the test closer to the bedside, the National Research Council of Canada (NRC) developed a portable device they called PowerBlade that uses a drop of blood and an automated sequence of steps to efficiently detect sepsis. Tested with 30 patients, the device was 92 per cent accurate in identifying patients at high risk of sepsis and 89 per cent accurate in ruling out those not at risk.
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Source: University of British Columbia
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