Factors affecting feeding ability in children with neonatal intensive care unit stay: a cluster analysis using machine learning methods - Feng, Jinwei; Shu, Tian; Li, Ruihao; Feng, Xuan; Huang, Yi; Cao, Jianguo; Peng, Kanglong (Frontiers in Pediatrics, 2025)
ObjectivesOral feeding introduction is challenging in Neonates Intensive Care Unit (NICU) daily care with limited measuring methods. Our study aimed to depict the oral feeding related features in neonates with critical conditions who were administered to NICU and its major predictors.Study designA total of 1,419 neonates with critical conditions who were administered to NICU were enrolled. The related features were acquired by using the Preterm Infant Oral Feeding readiness assessment scale (PIOFRA). The Shapley Additive Explanation (SHAP) values were used in XGBoost models established based on selected features. In addition, the ANOVA analysis was adopted to depict the group differences.ResultsThree profiles with distinct PIOFRA features were identified in cluster analysis (p > 0.05). Compared to other prediction models (e.g., Logistic Regression, Random Forest), the XGBoost model achieved the highest accuracy (85.2%). Sucking power and rooting reflex were identified as the features with largest impact in oral feeding predations that exhibited positive and negative influence respectively.ConclusionsOral feeding difficulty can be commonly observed in neonates in NICU, and more detailed assessments are needed to illustrate the difference in gestational features (e.g., born weight, gestational age) between difference profiles. PIOFRA features can be strong predictors in predicting whether neonates had achieved full oral feedings or not. However, more studies are needed to verify the detailed mechanism to illustrate how sucking and rooting reflex functions ensure the safe and efficient content transportation in neonates administered to NICU.