Closed loop construction of hypoglycemia risk management for high risk neonates in mother infant rooming in settings: a retrospective study with an embedded clinical decision support system.

Objective: To evaluate the effectiveness of an intelligent clinical decision support system (CDSS) for neonatal hypoglycemia management in mother-infant rooming-in settings, and to dissect the differential hypoglycemia risk conferred by individual high-risk factors and their specific combinations under standardized surveillance. Methods: A multidisciplinary team developed a knowledge-driven CDSS grounded in national expert consensus, integrating automated maternal-neonatal risk identification, dynamic tiered monitoring reminders, and structured stratified management recommendations. Effectiveness was assessed using a pre-post self-controlled analysis (historical control: January-March 2024, Results: CDSS implementation significantly reduced hypoglycemia incidence in both the pre-post (5.76% vs. 11.88%, Conclusion: The intelligent CDSS effectively reduces neonatal hypoglycemia in rooming-in settings. Hypoglycemia risk depends more on the specific types and combinations of high-risk factors than on their quantity alone, providing evidence for precise risk stratification. This closed-loop, guideline-driven workflow enhances clinical standardization and patient safety. Future multicenter studies incorporating machine learning and long-term neurodevelopmental follow-up are warranted.