Daniel Balcarcel
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Daniel Balcarcel has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Adam S. Himebauch
Division of Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA
1 shared publication - Javier J. Lasa
Divisions of Cardiology and Critical Care Medicine, Children’s Health, UT Southwestern Medical Center, Dallas, TX
1 shared publication - John P. Reilly
Division of Pulmonary, Allergy, and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
1 shared publication - Melania M. Bembea
Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
1 shared publication - Mike Regan
Extracorporeal Membrane Oxygenation Center, Children’s Hospital of Philadelphia, Philadelphia, PA
1 shared publication - Morgann Loaec
Division of Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA
1 shared publication
Latest Publications
- 29 October 2026
- Published by Wolters Kluwer Health in Critical Care Medicine
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 Organization Registry
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.
- 29 October 2026
- Published by Wolters Kluwer Health in Critical Care Medicine
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 Organization Registry
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.