Ryan P Barbaro1, Robert H Bartlett2, Rachel L Chapman3, Matthew L Paden4, Lloyd A Roberts5, Achamyeleh Gebremariam6, Gail M Annich7, Matthew M Davis8. 1. Department of Pediatrics, University of Michigan, Ann Arbor, MI; Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor, MI. Electronic address: barbaror@med.umich.edu. 2. Department of Surgery, University of Michigan, Ann Arbor, MI. 3. Department of Pediatrics, University of Southern California, Los Angeles and Center for Fetal and Neonatal Medicine, Children's Hospital Los Angeles, Los Angeles, CA. 4. Division of Pediatric Critical Care, Emory University, Atlanta, GA. 5. Intensive Care Department, Alfred Hospital, Monash University, Melbourne, Australia; School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia. 6. Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor, MI. 7. Critical Care Medicine, University of Toronto, Toronto, Canada. 8. Department of Pediatrics, University of Michigan, Ann Arbor, MI; Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, University of Michigan, Ann Arbor, MI; Gerald R. Ford School of Public Policy and School of Public Health, University of Michigan, Ann Arbor, MI.
Abstract
OBJECTIVE: To develop and validate the Neonatal Risk Estimate Score for Children Using Extracorporeal Respiratory Support, which estimates the risk of in-hospital death for neonates prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. STUDY DESIGN: We used an international ECMO registry (2008-2013); neonates receiving ECMO for respiratory support were included. We divided the registry into a derivation sample and internal validation sample, by calendar date. We chose candidate variables a priori based on published evidence of association with mortality; variables independently associated with mortality in logistic regression were included in this parsimonious model of risk adjustment. We evaluated model discrimination with the area under the receiver operating characteristic curve (AUC), and we evaluated calibration with the Hosmer-Lemeshow goodness-of-fit test. RESULTS: During 2008-2013, 4592 neonates received ECMO respiratory support with mortality of 31%. The development dataset contained 3139 patients treated in 2008-2011. The Neo-RESCUERS measure had an AUC of 0.78 (95% CI 0.76-0.79). The validation cohort had an AUC = 0.77 (0.75-0.80). Patients in the lowest risk decile had an observed mortality of 7.0% and a predicted mortality of 4.4%, and those in the highest risk decile had an observed mortality of 65.6% and a predicted mortality of 67.5%. CONCLUSIONS: Neonatal Risk Estimate Score for Children Using Extracorporeal Respiratory Support offers severity-of-illness adjustment for neonatal patients with respiratory failure receiving ECMO. This score may be used to adjust patient survival to assess hospital-level performance in ECMO-based care.
OBJECTIVE: To develop and validate the Neonatal Risk Estimate Score for Children Using Extracorporeal Respiratory Support, which estimates the risk of in-hospital death for neonates prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support. STUDY DESIGN: We used an international ECMO registry (2008-2013); neonates receiving ECMO for respiratory support were included. We divided the registry into a derivation sample and internal validation sample, by calendar date. We chose candidate variables a priori based on published evidence of association with mortality; variables independently associated with mortality in logistic regression were included in this parsimonious model of risk adjustment. We evaluated model discrimination with the area under the receiver operating characteristic curve (AUC), and we evaluated calibration with the Hosmer-Lemeshow goodness-of-fit test. RESULTS: During 2008-2013, 4592 neonates received ECMO respiratory support with mortality of 31%. The development dataset contained 3139 patients treated in 2008-2011. The Neo-RESCUERS measure had an AUC of 0.78 (95% CI 0.76-0.79). The validation cohort had an AUC = 0.77 (0.75-0.80). Patients in the lowest risk decile had an observed mortality of 7.0% and a predicted mortality of 4.4%, and those in the highest risk decile had an observed mortality of 65.6% and a predicted mortality of 67.5%. CONCLUSIONS:Neonatal Risk Estimate Score for Children Using Extracorporeal Respiratory Support offers severity-of-illness adjustment for neonatalpatients with respiratory failure receiving ECMO. This score may be used to adjust patient survival to assess hospital-level performance in ECMO-based care.
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