Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study.

Journal: BMJ paediatrics open
Published Date: May 14, 2025

Abstract

BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. Existing risk scores and criteria for paediatric sepsis are not well-suited for early diagnosis in ED.

Authors

  • Sylvester Gomes
    Evelina London Children's Hospital, London, UK sylvester.gomes@gstt.nhs.uk.
  • Harpreet Dhanoa
    Clinical Analytics, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Phil Assheton
    Clinical Analytics, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Ewan Carr
    Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
  • Damian Roland
    Health Sciences, University of Leicester, Leicester, UK.
  • Akash Deep
    Paediatric Intensive Care, King's College Hospital, London, UK.

Keywords

External Resources

Popular Topics
Recent Journals