A quality improvement initiative for neonatal hypoglycemia screening and management in a level III neonatal intensive care unit.

Objective: To bring screening and management of neonatal hypoglycemia in alignment with the 2011 AAP hypoglycemia clinical report METHODS: A multidisciplinary team developed a quality improvement initiative for neonatal hypoglycemia in neonates ≥35 weeks gestational age in a Level III neonatal intensive care unit between July 2020 and December 2021. A key driver diagram identified interventions for plan-do-study-act testing with corresponding measures to implement a hypoglycemia management protocol and improve adherence to AAP guidelines.

Results: Time to first blood glucose measurement increased from 49.

Open-Source Artificial Intelligence System Supports Diagnosis of Mendelian Diseases in Acutely Ill Infants.

Mendelian disorders are prevalent in neonatal and pediatric intensive care units and are a leading cause of morbidity and mortality in these settings. Current diagnostic pipelines that integrate phenotypic and genotypic data are expert-dependent and time-intensive. Artificial intelligence (AI) tools may help address these challenges.

A novel variant resulting in Fanconi anemia identified in an infant with multiple congenital anomalies.

Fanconi anemia, FA, is a rare, multi-system disease caused by pathogenic variants in DNA repair genes. We report a novel variant in an infant with FA whose tracheobronchomalacia has not been described in FA. His severe presentation expands the phenotype of -associated FA, reported only in three patients previously.

Analysis of the Perinatal Care System in a Remote and Mountainous District of Nepal.

Introduction: Despite significant improvements in recent years, maternal and neonatal health outcomes remain poor in many regions of the world. One such area is in the remote mountainous regions of Nepal. The purpose of this study is to describe the current antenatal care practices and delivery support in a mountainous district of Nepal.