Development and Validation of the Neonatal Risk Estimate Score for Children Using Extracorporeal Respiratory Support

• Type of Material: Article
• Authors: Ryan P. Barbaro, University of Michigan; Robert H. Bartlett, University of Michigan; Rachel L. Chapman, University of Southern California; Matthew Paden, Emory University; Lloyd A. Roberts, Alfred Hospital; Achamyeleh Gebremariam, University of Michigan; Gail M. Annich, University of Toronto; Matthew M. Davis, University of Michigan
• Language: English
• Date: 2016-03-19
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016 Elsevier Inc. All rights reserved.
• Final Published Version (URL): http://dx.doi.org/10.1016/j.jpeds.2016.02.057
• Title of Journal or Parent Work: Journal of Pediatrics
• ISSN: 0022-3476
• Volume: 173
• Start Page: 56
• End Page: +
• Grant/Funding Information: Supported by the Extracorporeal Life Support Organization. R.B. was supported by the Eunice Kennedy Shriver National Institute for Child Health and Human Development (T32 HD007534 [PI: M.D.]) and the Extracorporeal Life Support Organization.
• Keywords: MEMBRANE-OXYGENATION; ADJUSTMENT; PEDIATRIC-INTENSIVE-CARE; MODEL; MORTALITY; Pediatrics; LIFE-SUPPORT; FAILURE; UPDATE; SURVIVAL; PREDICTION; Science & Technology; Life Sciences & Biomedicine
• Research Categories: Health Sciences, Medicine and Surgery

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.