Ryan P Barbaro1,2, Philip S Boonstra3, Matthew L Paden4, Lloyd A Roberts5, Gail M Annich6, Robert H Bartlett7, Frank W Moler8, Matthew M Davis9,8,10,11. 1. Department of Pediatrics, University of Michigan, 1500 East Medical Center Drive, Mott F-6790/Box 5243, Ann Arbor, MI, 48109, USA. barbaror@med.umich.edu. 2. Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor, USA. barbaror@med.umich.edu. 3. School of Public Health Department of Biostatistics, University of Michigan, Ann Arbor, USA. 4. Division of Pediatric Critical Care, Emory University, Atlanta, GA, USA. 5. Intensive Care Department, Alfred Hospital and School of Public Health and Preventative Medicine, Monash University Melbourne, Clayton, Australia. 6. Critical Care Medicine, University of Toronto, Toronto, Canada. 7. Department of Surgery, University of Michigan, Ann Arbor, USA. 8. Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor, USA. 9. Department of Pediatrics, University of Michigan, 1500 East Medical Center Drive, Mott F-6790/Box 5243, Ann Arbor, MI, 48109, USA. 10. Department of Internal Medicine, University of Michigan, Ann Arbor, USA. 11. Gerald R. Ford School of Public Policy and Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, USA.
Abstract
PURPOSE: To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. METHODS: This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model's ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic. RESULTS: From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre-ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634. CONCLUSIONS: Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool.
PURPOSE: To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. METHODS: This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model's ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic. RESULTS: From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre-ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634. CONCLUSIONS: Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool.
Entities:
Keywords:
Extracorporeal membrane oxygenation; Mortality; Pediatric; Risk adjustment; Risk assessment; Severity of illness index
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