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Phenotyping Sepsis at Emergency Department Presentation Using Early Clinical Data: A Multicenter Cohort Study
Junhyuk Seo1, Namkee Oh2, Gee Young Suh3,4
1Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.
Shock (Augusta, Ga.)
|August 4, 2026
Summary
Sepsis phenotyping in the emergency department identified six patient groups based on routine variables. This approach reveals distinct clinical signatures and helps differentiate appropriate treatment delays from necessary interventions.
Area of Science:
- Emergency Medicine
- Critical Care Medicine
- Data Science in Healthcare
Background:
- Sepsis management is challenging due to its heterogeneity and limited early information.
- Dynamic clinical trajectories in sepsis require nuanced approaches for effective emergency department (ED) care.
Purpose of the Study:
- To develop and validate a sepsis phenotyping model using routine ED variables.
- To identify distinct patient phenotypes for improved understanding of sepsis severity and management.
Main Methods:
- K-means clustering applied to nine routine ED variables (demographics, vitals, frailty, mental status, lactate) from the Korean Sepsis Alliance (KSA) registry.
- Model developed in KSA 3 (2019-2021) and validated in the independent KSA 5 cohort (2022-2023).
- Phenotypes compared on 7-day mortality, sepsis-bundle compliance, and SOFA trajectories; stability assessed via bootstrap resampling.
Main Results:
- Six sepsis phenotypes identified in 9,430 patients, reproduced in 7,184, with mortality ranging from 6.7% to 31.8%.
- Extreme-severity phenotypes were robust, while intermediate phenotypes indicated a continuous severity spectrum.
- Non-compliance analysis revealed differences in appropriate withholding versus urgency-associated delays across phenotypes.
Conclusions:
- ED-based phenotyping using routine data identifies six sepsis signatures along a severity spectrum, not distinct subtypes.
- Decomposing bundle non-compliance highlights phenotype-specific proportions of withholding and delay.
- Findings support phenotype-stratified resuscitation strategies requiring prospective evaluation.