EHRs help identify patients at greatest risk of dying from sepsis

MartinaMartina Administrator admin
edited January 2019 in Sepsis

Drexel University researchers have developed an analytical model for detecting early warning signs of sepsis that can predict those patients at the greatest risk of dying from the life-threatening condition.

Leveraging EHR data from more than 210,000 hospital visits between 2013 and 2016, researchers have used their model to analyze the relationship between in-hospital mortality and sepsis symptoms with seven organ systems—cardiovascular, gastrointestinal, hematopoietic, metabolic, nervous, renal, and respiratory—in order to determine which organ dysfunctions resulted in deaths.

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