Development of the Pediatric Extracorporeal Membrane Oxygenation Prediction Model for Risk-Adjusting Mortality

David K Bailly1, Ron W Reeder1, Melissa Winder2

  • 1Division of Pediatric Critical Care, Department of Pediatrics, University of Utah, Salt Lake City, UT.

Insights

A new model predicts mortality risk for children needing extracorporeal membrane oxygenation (ECMO). This tool helps assess outcomes and compare centers for pediatric ECMO care.

Area of Science:

  • Pediatric Critical Care Medicine
  • Cardiopulmonary Support
  • Biostatistics

Background:

  • Extracorporeal membrane oxygenation (ECMO) is a life-support measure for critically ill children.
  • Accurate prediction of mortality is crucial for risk-adjusted outcome assessment in pediatric ECMO centers.
  • Existing models may not adequately capture the complexities of pediatric ECMO patients.

Purpose of the Study:

  • To develop and validate a prognostic model for predicting in-hospital mortality at the initiation of ECMO in children.
  • To provide a tool for risk stratification and benchmarking of outcomes across pediatric ECMO centers.

Main Methods:

  • Utilized multivariable logistic regression on a large national cohort of pediatric ECMO patients.
  • Included data from 514 children (<19 years) across eight tertiary care children's hospitals.
  • Model variables included age, ECMO indication, meconium aspiration, congenital diaphragmatic hernia, bloodstream infection, arterial pH, PTT, and INR.

Main Results:

  • Overall mortality was 45% (n=232) in the cohort.
  • Documented bloodstream infection (OR 5.26) and extracorporeal cardiopulmonary resuscitation (OR 4.36) were significant predictors of mortality.
  • The Pediatric Extracorporeal Membrane Oxygenation Prediction model achieved a C-statistic of 0.75 (95% CI, 0.70-0.80).

Conclusions:

  • The developed Pediatric Extracorporeal Membrane Oxygenation Prediction model accurately predicts in-hospital mortality for pediatric ECMO patients.
  • This model serves as a valuable tool for risk stratification and benchmarking ECMO outcomes across different pediatric centers.
  • It is the first comprehensive risk stratification model for pediatric ECMO indications.
Abstract

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