About This Event
Sepsis remains a leading cause of pediatric mortality, and early identification is critical but limited as existing models inadequately predict risk before organ dysfunction develops. Using a large multicenter emergency department population, Lurie Children’s Hospital of Chicago developed and validated machine learning models to predict future sepsis and septic shock based on electronic health record data from the first four hours of care. In the ED, the models can identify children who have not yet developed sepsis and may be useful in future implementation work to identify children at risk.
