Unsupervised Machine Learning in Identification of Septic Shock Phenotypes and Their In-Hospital Outcomes: A Multicenter Cohort Study

Abstract excerpt

Background: Septic shock is a heterogeneous syndrome with diverse clinical presentations and pathophysiology, yet current management guidelines largely treat it as a homogenous entity. Early risk stratification relies on lactate and different predictive scoring systems, which may not capture the underlying heterogeneity in host responses. Aim: To identify discrete subphenotypes of septic shock using admission...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Bacterial Identification and Susceptibility Testing
• Share to Sepsis Diagnosis and Treatment