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Related Experiment Video

Updated: Sep 16, 2025

Author Spotlight: Enhancing Understanding and Treatment Strategies with the NEC-on-a-Chip Model
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Fulminant necrotizing enterocolitis: clinical features and a predictive model.

Xiaoyu Chen1, Yuqiao Li2, Yuhan Liu2

  • 1Department of Hematology/Oncology, Children's Hospital of Soochow University, Suzhou, China.

BMC Pediatrics
|July 10, 2025
PubMed
Summary

This study developed a predictive model for fulminant necrotizing enterocolitis (fNEC) in infants. The nomogram, using clinical factors, accurately identifies infants at high risk for this severe condition.

Keywords:
Fulminant necrotizing EnterocolitisNomogramPredictive modelPreterm infants

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Area of Science:

  • Neonatalogy
  • Pediatric Surgery

Background:

  • Necrotizing enterocolitis (NEC) is a serious condition in neonates.
  • Fulminant NEC (fNEC) represents a severe subset of NEC with higher morbidity and mortality.
  • Predictive tools for fNEC are crucial for timely intervention.

Purpose of the Study:

  • To develop and validate a nomogram for predicting fNEC risk in infants diagnosed with NEC.
  • To identify and summarize the distinct clinical features associated with fNEC.

Main Methods:

  • A cohort of 315 neonates diagnosed with NEC was divided into training and validation sets.
  • Logistic regression analysis identified independent risk factors for fNEC.
  • A nomogram model was constructed and evaluated using AUC, calibration curves, and decision curve analysis (DCA).

Main Results:

  • Neonates with fNEC presented with more severe symptoms, including acidosis, thrombocytopenia, absent bowel sounds, and required more surgical interventions.
  • The nomogram incorporated predictors: bloody stool, absent bowel sounds, elevated lactate, and low pH.
  • The model demonstrated high predictive accuracy with AUCs of 0.939 (training) and 0.975 (validation).

Conclusions:

  • fNEC is associated with significantly more severe clinical manifestations and higher mortality.
  • The developed nomogram model shows strong potential to aid clinicians in predicting fNEC risk in neonates.