Predictors of Neonatal Intensive Care Unit Admission and Adverse Outcomes Related to Gestational Diabetes

Gestational diabetes mellitus (GDM) is a type of diabetes that manifests itself in pregnant women. It poses a significant risk to the mother's health as well as the health of the infant, including more babies being brought to the neonatal intensive care unit (NICU). It puts both the mother's and the child's health at serious risk, increasing the likelihood that newborns may need to be treated in a neonatal critical care unit. This study aimed to determine the factors that predict GDM-related NICU admission and other adverse newborn outcomes. The study was a cross-sectional analysis of 175 pregnant women who presented with gestational diabetes at the Maternity and Children's Hospital in Bisha (MCH-Bisha), Saudi Arabia, between January 1 and December 31, 2022. A logistic regression model was used to analyze the data to predict adverse outcomes for newborns and NICU admissions and identify associations between maternal variables and outcomes. Maternal characteristics highly associated with adverse neonatal outcomes included advanced maternal age (greater than 30 years), a family history of DM, and a history of greater than or equal to four previous pregnancies. Logistic regression models revealed that newborns delivered to mothers older than 30 years were 7.17 times more likely to be admitted to the NICU than newborns born to mothers younger than 30 years. Saudi nationality, urban residence, and cesarean section delivery factors account for nearly all adverse neonatal outcomes (91%, 75%, and 91%, respectively). Newborns delivered by cesarean section were 3.38 times more likely to be admitted to NICU, and the association was significant. Maternal age greater than 30 years and a history of more than or equal to four pregnancies were the strongest indicators of infant adverse outcomes and NICU admittance among women with gestational diabetes. These findings highlight the need for approaches to GDM management that are efficient, thorough, and multidisciplinary.