Development and Validation of a Mortality Prediction Model in Extremely Low Gestational Age Neonates.

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.