Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019

• Published in: Critical care medicine Vol. 48; no. 2; p. 210
• Main Authors: Reyna, Matthew A, Josef, Christopher S, Jeter, Russell, Shashikumar, Supreeth P, Westover, M Brandon, Nemati, Shamim, Clifford, Gari D, Sharma, Ashish
• Format: Journal Article
• Language: English
• Published: United States 01.02.2020
• Subjects: Algorithms; Early Diagnosis; Electronic Health Records; Female; Humans; Intensive Care Units; Male; Sepsis - diagnosis; Sepsis - physiopathology; Severity of Illness Index; Time Factors; United States; United States

Sepsis is a major public health concern with significant morbidity, mortality, and healthcare expenses. Early detection and antibiotic treatment of sepsis improve outcomes. However, although professional critical care societies have proposed new clinical criteria that aid sepsis recognition, the fun...