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EHRs help identify patients at greatest risk of dying from sepsis

November 28, 2018

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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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