OBJECTIVE: Outcomes analysis in congenital diaphragmatic hernia (CDH) requires a validated risk-adjustment tool. The purpose of this study was to use the Canadian Neonatal Network (CNN) database to validate the Score for Neonatal Acute Physiology, Version II (SNAP-II) for prediction of mortality among CDH infants admitted to a neonatal intensive care unit (NICU), and to compare this to the predictive equation recently developed by the Congenital Diaphragmatic Hernia Study Group (CDHSG). STUDY DESIGN: Infants with CDH in the CNN database were identified. Bivariate and multivariable logistic regression models were used to identify risk factors predictive of mortality. Model predictive performance and calibration were assessed using the area under the receiver operator characteristic curve and the technique of Hosmer-Lemeshow, respectively, and compared with the CDHSG predictive equation. RESULTS: There were 88 patients with CDH among 19,507 admissions to CNN hospitals. The mortality rate among CDH patients surviving to NICU admission was 17%, and 12.5% received extracorporeal membrane oxygenation therapy. Gestational age and admission SNAP-II score predicted mortality. Model predictive performance and calibration were optimized with these variables combined. The CDHSG equation was equally predictive of mortality, but was only marginally calibrated. CONCLUSIONS: SNAP-II is highly predictive of mortality among patients with CDH, and can be used to risk-adjust these patients.
OBJECTIVE: Outcomes analysis in congenital diaphragmatic hernia (CDH) requires a validated risk-adjustment tool. The purpose of this study was to use the Canadian Neonatal Network (CNN) database to validate the Score for Neonatal Acute Physiology, Version II (SNAP-II) for prediction of mortality among CDHinfants admitted to a neonatal intensive care unit (NICU), and to compare this to the predictive equation recently developed by the Congenital Diaphragmatic Hernia Study Group (CDHSG). STUDY DESIGN:Infants with CDH in the CNN database were identified. Bivariate and multivariable logistic regression models were used to identify risk factors predictive of mortality. Model predictive performance and calibration were assessed using the area under the receiver operator characteristic curve and the technique of Hosmer-Lemeshow, respectively, and compared with the CDHSG predictive equation. RESULTS: There were 88 patients with CDH among 19,507 admissions to CNN hospitals. The mortality rate among CDHpatients surviving to NICU admission was 17%, and 12.5% received extracorporeal membrane oxygenation therapy. Gestational age and admission SNAP-II score predicted mortality. Model predictive performance and calibration were optimized with these variables combined. The CDHSG equation was equally predictive of mortality, but was only marginally calibrated. CONCLUSIONS: SNAP-II is highly predictive of mortality among patients with CDH, and can be used to risk-adjust these patients.
Authors: Jill G Zwicker; Ruth E Grunau; Elysia Adams; Vann Chau; Rollin Brant; Kenneth J Poskitt; Anne Synnes; Steven P Miller Journal: Pediatr Neurol Date: 2013-02 Impact factor: 3.372
Authors: Andrea Gentili; Rosina De Rose; Elisa Iannella; Maria Letizia Bacchi Reggiani; Mario Lima; Simonetta Baroncini Journal: Int J Pediatr Date: 2012-01-04