Variation in Pediatric Extracorporeal Cardiopulmonary Resuscitation Survival After In-Hospital Cardiac Arrest: Development and Validation of a Survival Model for Risk-Standardized Survival Rates: An Analysis of the Extracorporeal Life Support Organiz

OBJECTIVES: To develop and internally validate a multivariable prediction model for survival to hospital discharge after pediatric extracorporeal cardiopulmonary resuscitation (ECPR) for in-hospital cardiac arrest (IHCA), and to use this model to derive risk-standardized survival rates (RSSRs) and quantify between-hospital variation in outcomes. DESIGN: Retrospective multicenter cohort study. SETTING: Hospitals contributing to the Extracorporeal Life Support Organization (ELSO) registry between 2020 and 2023. PATIENTS: Children (< 18 yr) treated with ECPR for IHCA. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eligible patients were identified from the ELSO Registry and split into derivation (N = 1060) and validation (N = 317) cohorts using a hospital-stratified split to preserve within-hospital clustering. Survival prediction models were derived using penalized logistic regression with the least absolute shrinkage and selection operator. A full-event model incorporating 14 routinely available clinical variables demonstrated fair discrimination (area under the curve, 0.728 in the derivation cohort and 0.678 in the validation cohort) and good calibration (observed-to-expected ratio, 0.995; Brier score, 0.222 in the validation cohort). This model was embedded in a multilevel logistic regression model to generate hospital-level RSSRs for centers reporting five or more ECPR cases. Between-hospital variation was quantified using the median odds ratio, which was 1.30 (95% CI, 1.11-1.93), indicating significant differences in survival likelihood between centers after adjusting for patient-level risk. CONCLUSIONS: In a large, international cohort of pediatric ECPR patients, we developed and internally validated a clinically interpretable model for survival to hospital discharge. The model performance as a discriminator likely limits its use as a standalone tool for clinical decision-making. However, strong internal calibration allowed for determination of hospital-level RSSRs, which revealed significant inter-hospital variability. These findings demonstrate the feasibility of developing a risk-adjustment model capable of estimating hospital-level RSSRs. Additional external validation and evaluation of residual case-mix differences are needed before such models can be used for benchmarking across pediatric ECPR centers.

Authors

Institutions

Publication Details

Journal
Critical Care Medicine
Published
2026-10-29
DOI
https://doi.org/10.1097/ccm.0000000000007383
Primary Topic
Cardiac Arrest and Resuscitation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Variation in Pediatric Extracorporeal Cardiopulmonary Resuscitation Survival After In-Hospital Cardiac Arrest: Development and Validation of a Survival Model for Risk-Standardized Survival Rates: An Analysis of the Extracorporeal Life Support Organiz

Adam S. Himebauch, Ryan W. Morgan, Todd J. Kilbaugh, Ravi R. Thiagarajan et al.
3 links
Critical Care Medicine
Cardiac Arrest and Resuscitation
article

Variation in Pediatric Extracorporeal Cardiopulmonary Resuscitation Survival After In-Hospital Cardiac Arrest: Development and Validation of a Survival Model for Risk-Standardized Survival Rates: An Analysis of the Extracorporeal Life Support Organiz

Adam S. Himebauch, Ryan W. Morgan, Todd J. Kilbaugh, Ravi R. Thiagarajan, Melania M. Bembea, Morgann Loaec, 冯 瑞, Daniel R. Balcarcel, Javier J. Lasa, John P. Reilly, Robert M Sutton, Mike Regan
article en

Abstract

OBJECTIVES: To develop and internally validate a multivariable prediction model for survival to hospital discharge after pediatric extracorporeal cardiopulmonary resuscitation (ECPR) for in-hospital cardiac arrest (IHCA), and to use this model to derive risk-standardized survival rates (RSSRs) and quantify between-hospital variation in outcomes. DESIGN: Retrospective multicenter cohort study. SETTING: Hospitals contributing to the Extracorporeal Life Support Organization (ELSO) registry between 2020 and 2023. PATIENTS: Children (< 18 yr) treated with ECPR for IHCA. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eligible patients were identified from the ELSO Registry and split into derivation (N = 1060) and validation (N = 317) cohorts using a hospital-stratified split to preserve within-hospital clustering. Survival prediction models were derived using penalized logistic regression with the least absolute shrinkage and selection operator. A full-event model incorporating 14 routinely available clinical variables demonstrated fair discrimination (area under the curve, 0.728 in the derivation cohort and 0.678 in the validation cohort) and good calibration (observed-to-expected ratio, 0.995; Brier score, 0.222 in the validation cohort). This model was embedded in a multilevel logistic regression model to generate hospital-level RSSRs for centers reporting five or more ECPR cases. Between-hospital variation was quantified using the median odds ratio, which was 1.30 (95% CI, 1.11-1.93), indicating significant differences in survival likelihood between centers after adjusting for patient-level risk. CONCLUSIONS: In a large, international cohort of pediatric ECPR patients, we developed and internally validated a clinically interpretable model for survival to hospital discharge. The model performance as a discriminator likely limits its use as a standalone tool for clinical decision-making. However, strong internal calibration allowed for determination of hospital-level RSSRs, which revealed significant inter-hospital variability. These findings demonstrate the feasibility of developing a risk-adjustment model capable of estimating hospital-level RSSRs. Additional external validation and evaluation of residual case-mix differences are needed before such models can be used for benchmarking across pediatric ECPR centers.

Critical Care Medicine
Boston Children's Hospital (US), Children's Hospital of Philadelphia (US), Johns Hopkins University (US), Johns Hopkins Medicine (US), University of Pennsylvania (US), The University of Texas Southwestern Medical Center (US)
Good health and well-being
Openalex Percentile: Top 10%
Cardiac Arrest and Resuscitation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon