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Published on: October 24, 2018
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.
Objectives:
To develop a prognostic model for predicting mortality at time of extracorporeal membrane oxygenation initiation for children which is important for determining center-specific risk-adjusted outcomes.
Design:
Multivariable logistic regression using a large national cohort of pediatric extracorporeal membrane oxygenation patients.
Setting:
The ICUs of the eight tertiary care children's hospitals of the Collaborative Pediatric Critical Care Research Network.
Patients:
Five-hundred fourteen children (< 19 yr old), enrolled with an initial extracorporeal membrane oxygenation run for any indication between January 2012 and September 2014.
Interventions:
None.
Measurements And Main Results:
A total of 514 first extracorporeal membrane oxygenation runs were analyzed with an overall mortality of 45% (n = 232). Weighted logistic regression was used for model selection and internal validation was performed using cross validation. The variables included in the Pediatric Extracorporeal Membrane Oxygenation Prediction model were age (pre-term neonate, full-term neonate, infant, child, and adolescent), indication for extracorporeal membrane oxygenation (extracorporeal cardiopulmonary resuscitation, cardiac, or respiratory), meconium aspiration, congenital diaphragmatic hernia, documented blood stream infection, arterial blood pH, partial thromboplastin time, and international normalized ratio. The highest risk of mortality was associated with the presence of a documented blood stream infection (odds ratio, 5.26; CI, 1.90-14.57) followed by extracorporeal cardiopulmonary resuscitation (odds ratio, 4.36; CI, 2.23-8.51). The C-statistic was 0.75 (95% CI, 0.70-0.80).
Conclusions:
The Pediatric Extracorporeal Membrane Oxygenation Prediction model represents a model for predicting in-hospital mortality among children receiving extracorporeal membrane oxygenation support for any indication. Consequently, it holds promise as the first comprehensive pediatric extracorporeal membrane oxygenation risk stratification model which is important for benchmarking extracorporeal membrane oxygenation outcomes across many centers.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

