What question did this study set out to answer?

This research aims to develop a framework for identifying clinically relevant sub-phenotypes in sepsis patients.

March 21, 2026Open Access

Prediction-guided clustering for sepsis phenotyping: a retrospective cohort analysis

Key Points

This research aims to develop a framework for identifying clinically relevant sub-phenotypes in sepsis patients.
Conducted a retrospective cohort analysis of sepsis patients.
Implemented a prediction-guided clustering framework.
Assessed clinical interpretability of identified sub-phenotypes.
Identified clinically meaningful sub-phenotypes among sepsis patients.
Proposed an effective strategy for personalized medicine.
Demonstrated potential for improved patient outcomes through tailored treatment approaches.

Abstract

This study introduces a flexible and effective framework for the identification of robust and clinically meaningful sub-phenotypes within the population of sepsis patients. Moreover, the identified sub-phenotypes are clinically interpretable, and the proposed trajectory-aware phenotyping approach may support the future development of personalised and precision medicine strategies.

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Authors

Paul Hilders

Amsterdam Neuroscience

Lada Lijović

University Hospital Centre Zagreb

Martijn Otten

Amsterdam Neuroscience

Journals

Intensive Care Medicine Experimental

Actions

Institutions

University of Cambridge

Vrije Universiteit Amsterdam

Leiden University Medical Center

References and Citations

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Prediction-guided clustering for sepsis phenotyping: a retrospective cohort analysis

Key Points

Abstract

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Discussion

Authors

Journals

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Institutions

References and Citations

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