Sepsis is the number 1 cause of death in hospitals. The FDA approval of IntelliSep, the first sepsis diagnostic tool, could change this.
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Each year, approximately 30 million US adults present to emergency departments with sepsis signs and symptoms.
Sepsis remains one of the most common and costly causes of death in the US, but 80% of these fatalities could be avoided with early diagnosis and treatment. Rapidly identifying and sepsis is vital to reduce costs and increase the likelihood of patient survival.
“IntelliSep is truly a game changer for sepsis because it provides a unique indicator that gets to the heart of the current sepsis definition, immune dysregulation,” explained Hollis O’Neal, MD, medical director of research at Our Lady of the Lake Regional Medical Center, and a critical care physician at LSU Health Sciences Center. “The test provides hospital staff with the information needed to identify and treat septic patients efficiently and reduce the financial and health burdens of overtreatment for hospitals and patients.”
IntelliSep is intended to help clinicians recognize sepsis in under 10 minutes. The emergency department-focused diagnostic tool can identify sepsis from a standard blood draw. IntelliSep classifies patients according to their likelihood of sepsis, ranging from Band 1 indicating low probability of sepsis to Band 3 indicating high probability of sepsis.
A 510(k) clearance, also known as Premarket Notification, demonstrates that the marketed device is safe and effective. The FDA clears the 510(k) when the submission has been proven to be at least as safe and effective as a similar legally marketed device.
IntelliSep assesses the body’s immune response to infection using immune cell morphology. Because the biophysical properties of white blood cells from sepsis patients change under pressure, the diagnostic tool identifies sepsis by applying pressure to tens of thousands of cells and observing the reaction. IntelliSep uses imaging to capture these changes and characterizes them with a proprietary algorithm, predicting the likelihood of sepsis.
