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Determining predictors of sepsis at triage among children under 5 years of age in resource-limited settings: A

Jollee S T Fung1,2, Samuel Akech3, Niranjan Kissoon1,4

  • 1Centre for International Child Health, BC Children's Hospital, Vancouver, BC, Canada.

Plos One
|January 29, 2019
PubMed

Insights

Early identification of sepsis in children is crucial. This study identified 45 key variables to develop a mobile tool for low-skilled workers to predict sepsis risk at triage.

Area of Science:

  • Pediatric critical care
  • Infectious disease epidemiology
  • Health informatics

Background:

  • Sepsis is a leading cause of mortality in children under five, necessitating early detection for timely intervention.
  • Identifying at-risk children upon presentation to healthcare facilities is critical for preventing multiorgan failure and death.
  • Existing diagnostic methods may not be readily available or suitable for low-resource settings.

Purpose of the Study:

  • To generate a consensus-driven list of predictor variables for a sepsis prediction model.
  • To develop a mobile health tool for use by low-skilled healthcare workers at triage.
  • To improve early identification and management of pediatric sepsis.

Main Methods:

  • Systematic literature review and analysis of global guidelines to identify initial candidate variables.
  • Modified Delphi process involving 26 international experts to refine the variable list.
  • Evaluation of variables based on predictive potential, measurement reliability, and resource requirements.

Main Results:

  • An initial list of 72 candidate predictor variables was generated.
  • A final list of 45 consensus-driven predictor variables was established through expert consensus.
  • The selected variables are suitable for use by low-skilled healthcare workers in diverse settings.

Conclusions:

  • The identified 45 predictor variables form the basis for a robust sepsis prediction model.
  • This model will be integrated into a mobile application for accessible triage decision support.
  • The tool aims to enhance early sepsis detection and improve outcomes for critically ill children.

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