US researchers develop Persevere test to stratify patients with sepsis

14 November 2019 (Last Updated November 14th, 2019 12:23)

Researchers at Cincinnati Children’s Hospital have developed and tested a rapid blood assay that measures five biomarkers and precisely predicts those patients who stand at low, medium or high risk for death from sepsis.

Researchers at Cincinnati Children’s Hospital have developed and tested a rapid blood assay that measures five biomarkers and precisely predicts those patients who stand at low, medium or high risk for death from sepsis.

The test, Persevere, enables doctors to identify and classify sepsis when the body is due to release the bacterial infection.

Upon understanding the five proteins / genes that make up the assay’s five-biomarker blood panel, doctors can commence immediate medical interventions.

Cincinnati Children’s Hospital critical care medicine director Hector Wong said that besides stratifying the patients into low, medium and high-risk groups, the biomarker test enables doctors to choose the right interventions for particular patients, including the drugs and dosages.

Wong, the study’s investigator, added: “The Persevere platform focuses on stratification and prognostication, not diagnostics. Prognostic enrichment is a fundamental tool of precision medicine. It allows us to predict the disease course and progression in individuals and tailor treatment to different groups of patients and individuals.”

The assay platform enables researchers to gain vital clues to analyse the underlying biological mechanisms of how sepsis commences, as well as how it is released into the body and how it can be prevented therapeutically.

Sepsis especially impacts fragile young children and the elderly hospitalised in intensive care units, killing over 200,000 individuals annually.

For over a decade, the tool has been in development by the researchers, who reduced the number of biomarkers in the assay platform from 80 down to five, making it easier to blend technologies such as computer-assisted biology and informatics with laboratory experimentation for therapies.