Alvaro Moreira1, Domenico Benvenuto2, Christopher Fox-Good1, Yasmeen Alayli1, Mary Evans1, Baldvin Jonsson3, Stellan Hakansson4, Nathan Harper5, Jennifer Kim1, Mikael Norman6, Matteo Bruschettini7. 1. Department of Pediatrics, University of Texas Health San Antonio, San Antonio, Texas, USA. 2. Department of Biostatistics, Epidemiology and Molecular Pathology, Università Campus Bio-Medico di Roma, Rome, Italy. 3. Department of Women's and Children's Health, Karolinska Institutet, Solna, Sweden. 4. Department of Clinical Sciences/Pediatrics, Umeå University, Umeå, Sweden. 5. Veterans Administration Research Center for AIDS and HIV-1 Infection and Center for Personalized Medicine, South Texas Veterans Health Care System, San Antonio, Texas, USA. 6. Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden. 7. Department of Pediatrics, Lund University, Lund, Sweden.
Abstract
INTRODUCTION: Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families. OBJECTIVE: The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, <28 weeks) neonates. METHODS: A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the receiver operating characteristic curve (AUC) and compared to validated mortality prediction models and an external cohort of neonates. RESULTS: Among 3,752 live-born extremely preterm infants (46% girls), in-hospital mortality was 18% (n = 685). The median gestational age and birth weight were 25.0 weeks (interquartile range [IQR] 24.0, 27.0) and 780 g (IQR 620, 940), respectively. The proposed model consisted of three variables: birth weight (grams), Apgar score at 5 min of age, and gestational age (weeks). The BAG model had an AUC of 76.9% with a 95% confidence interval (CI) (72.6%, 81.3%), while birth weight and gestational age had an AUC of 73.1% (95% CI: 68.4%,77.9%) and 71.3% (66.3%, 76.2%). In the validation cohort, the BAG model had an AUC of 68.9%. CONCLUSION: The BAG model is a new mortality prediction model in ELGA neonates that was developed using readily available information.
INTRODUCTION: Understanding factors that associate with neonatal death may lead to strategies or interventions that can aid clinicians and inform families. OBJECTIVE: The aim of the study was to develop an early prediction model of neonatal death in extremely low gestational age (ELGA, <28 weeks) neonates. METHODS: A predictive cohort study of ELGA neonates was derived from the Swedish Neonatal Quality Register between the years 2011 to May 2021. The goal was to use readily available clinical variables, collected within the first hour of birth, to predict in-hospital death. Data were split into a train cohort (80%) to build the model and tested in 20% of randomly selected neonates. Model performance was assessed via area under the receiver operating characteristic curve (AUC) and compared to validated mortality prediction models and an external cohort of neonates. RESULTS: Among 3,752 live-born extremely preterm infants (46% girls), in-hospital mortality was 18% (n = 685). The median gestational age and birth weight were 25.0 weeks (interquartile range [IQR] 24.0, 27.0) and 780 g (IQR 620, 940), respectively. The proposed model consisted of three variables: birth weight (grams), Apgar score at 5 min of age, and gestational age (weeks). The BAG model had an AUC of 76.9% with a 95% confidence interval (CI) (72.6%, 81.3%), while birth weight and gestational age had an AUC of 73.1% (95% CI: 68.4%,77.9%) and 71.3% (66.3%, 76.2%). In the validation cohort, the BAG model had an AUC of 68.9%. CONCLUSION: The BAG model is a new mortality prediction model in ELGA neonates that was developed using readily available information.
Authors: M M Pollack; M A Koch; D A Bartel; I Rapoport; R Dhanireddy; A A El-Mohandes; K Harkavy; K N Subramanian Journal: Pediatrics Date: 2000-05 Impact factor: 7.124
Authors: Louise Im Koller-Smith; Prakesh S Shah; Xiang Y Ye; Gunnar Sjörs; Yueping A Wang; Sharon S W Chow; Brian A Darlow; Shoo K Lee; Stellan Håkanson; Kei Lui Journal: BMC Pediatr Date: 2017-07-14 Impact factor: 2.125