Background: Neonatal hypoglycemia is a common and potentially serious metabolic disorder that can result in permanent neurodevelopmental impairment. Objective: To investigate the independent maternal and neonatal risk factors associated with the occurrence of neonatal hypoglycemia in the immediate postnatal period and to quantify their predictive strength using multivariate modeling. Methods: In this cohort study, 100 neonates at high risk for hypoglycemia were enrolled within the first 24 hours of life at a tertiary neonatal intensive care unit. Risk factors assessed included intrauterine growth restriction, infant of a diabetic mother, large for gestational age, gestational age, birth weight, mode of delivery, and maternal medical history. Blood glucose levels were measured via standardized capillary sampling at multiple time points during the first 12 hours of life. Logistic regression analysis was used to identify independent predictors of hypoglycemia, and model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and the Hosmer–Lemeshow goodness-of-fit test. Results: about 38% of neonates developed hypoglycemia within the first 12 hours of life. IUGR (adjusted odds ratio aOR 3.52, 95% CI: 1.47–8.44), maternal diabetes (aOR 2.89, 95% CI: 1.19–7.02), and cesarean delivery (aOR 2.21, 95% CI: 1.01–4.89) were identified as significant independent predictors. The final multivariate model demonstrated good discriminative ability (AUROC = 0.79) and calibration (Hosmer–Lemeshow p = 0.62), indicating reliable predictive performance. Conclusion: Specific maternal and neonatal factors—including IUGR, maternal diabetes, and mode of delivery—are strong independent predictors of neonatal hypoglycemia. These findings underscore the need for structured risk-based screening protocols to identify at-risk neonates early and allocate monitoring resources effectively.
Mahmoud et al. (Thu,) studied this question.