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<p>To construct a nomogram for feeding intolerance (FI) during therapeutic hypothermia (TH) in neonates with hypoxic-ischemic encephalopathy (HIE). 179 neonates with HIE were recruited between March 2017 and July 2023 and clinical data subjected to least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis. A predictive model was constructed and verified by receiver operating characteristic (ROC) curve analysis, calibration plots and decision curve analysis (DCA). Neonatal infection, 5-min Apgar score, hypoglycemia, time of enteral nutrition initiation, initial enteral feeding volume (15–30 mL/kg/day) and rate of feeding advancement (1–5 mL/kg/day) were found to be independent predictors for FI. Earlier initiation, larger initial volume and rapid feeding progression increased FI risk and slow advancement was protective. ROC analysis gave an area under the curve (AUC) of 0.83 (95% CI: 0.77–0.89) and internal verification concordance index (C-index) was 0.829. DCA showed a favorable net clinical benefit for the FI predictive model. The predictive model may identify the causes of FI at an early stage and inform clinical decisions.</p>

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Predictive model for feeding intolerance in neonates with hypoxic ischemic encephalopathy during therapeutic hypothermia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月3日

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  • Zhongping Shui,
  • Ying Liu,
  • Haimei Duan,
  • Qiuyi Sun,
  • Huan He,
  • Huayun He,
  • Jianhui Wang,
  • Huaying Yin

摘要

To construct a nomogram for feeding intolerance (FI) during therapeutic hypothermia (TH) in neonates with hypoxic-ischemic encephalopathy (HIE). 179 neonates with HIE were recruited between March 2017 and July 2023 and clinical data subjected to least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis. A predictive model was constructed and verified by receiver operating characteristic (ROC) curve analysis, calibration plots and decision curve analysis (DCA). Neonatal infection, 5-min Apgar score, hypoglycemia, time of enteral nutrition initiation, initial enteral feeding volume (15–30 mL/kg/day) and rate of feeding advancement (1–5 mL/kg/day) were found to be independent predictors for FI. Earlier initiation, larger initial volume and rapid feeding progression increased FI risk and slow advancement was protective. ROC analysis gave an area under the curve (AUC) of 0.83 (95% CI: 0.77–0.89) and internal verification concordance index (C-index) was 0.829. DCA showed a favorable net clinical benefit for the FI predictive model. The predictive model may identify the causes of FI at an early stage and inform clinical decisions.