Multicenter Validation of Clinical Sepsis Phenotypes
By
Chang Ho Yoon
Daniel Sjöholm
Kristin E. Wickstrøm
Anders Skyrud Danielsen
Christian Prebensen
John Karlsson Valik
Aleksander Rygh Holten
Erik Koldberg Amundsen
A. Sarah Walker
David W. Eyre
Valeria Vitelli
Pontus Nauclér
June 1, 2026
Clinical Scorecard: Validation of Clinical Sepsis Phenotypes Across Multiple Centers
At a Glance
Category Detail
Condition Key Mechanisms Dysregulated host response to infection leading to organ dysfunction. [Source needed] Target Population Care Setting
Key Highlights
Identification of 4 distinct sepsis phenotypes (α, β, γ, δ) using machine learning. [Source needed] Phenotypes defined by clinical and laboratory variables with different mortality risks. [Source needed] Study conducted in Oslo, Stockholm, and Oxford to validate SENECA phenotypes. [Source needed] Use of 29 variables for clustering, with adaptations for missing data. [Source needed] Consensus clustering method applied to derive site-specific clinical phenotypes. [Source needed] Guideline-Based Recommendations
Diagnosis
Management
Tailoring treatments based on identified sepsis phenotypes. [Source needed] Monitoring & Follow-up
Risks
Patient & Prescribing Data
Systemic antibiotics administered within 6 hours of admission. [Source needed]
Clinical Best Practices
Utilize standardized data collection methods for sepsis phenotyping. [Source needed] Implement machine learning techniques for clustering sepsis cases. [Source needed] Consider local epidemiologic factors when applying sepsis phenotypes. [Source needed] Related Resources & Content
