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Multicenter Study
. 2019 May;20(5):426-434.
doi: 10.1097/PCC.0000000000001882.

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

Affiliations
Multicenter Study

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

David K Bailly et al. Pediatr Crit Care Med. 2019 May.

Abstract

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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Conflict of interest statement

Copyright form disclosure: Drs. Bailly, Reeder, Pollack, Moler, Meert, Berg, Carcillo, Zuppa, Newth, Berger, Bell, Dean, Garcia-Filion, Wessel, Heidemann, Harrison, and Dalton received support for article research from the National Institutes of Health (NIH). Drs. Reeder, Pollack, Meert, Berger, Wessel, Heidemann, Doctor, Harrison, and Dalton’s institutions received funding from the NIH. Dr. Barbaro disclosed that he is the Extracorporeal Life Support Organization (ELSO) Registry Chair. Drs. Moler, Berg, Carcillo, Zuppa, Newth, Bell, and Dean’s institutions received funding from the National Institute of Child Health and Human Development. Dr. Moler’s institution also received funding from the National Heart, Lung, and Blood Institute. Dr. Carcillo’s institution also received funding from the National Institute of General Medical Sciences. Dr. Newth received funding from Philips Research North America. Dr. Berger’s institution also received funding from the Association of Pediatric Pulmonary Hypertension and Actelion. Dr. Nicholson disclosed government work. Dr. Doctor’s institution also received funding from the Department of Defense and Kalocyte. Dr. Dalton received funding from Innovative ECMO Concepts (consultant). Ms. Winder has disclosed that she does not have any potential conflicts of interest

Figures

Figure 1.
Figure 1.
Distribution of estimated probability of mortality (Panel A) and the calibration plot for observed to expected mortality by risk group (Panel B). An even distribution and good calibration is demonstrated across all risk groups.

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