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Author Spotlight: Enhancing Understanding and Treatment Strategies with the NEC-on-a-Chip Model
Published on: July 28, 2023
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Predicting surgical NEC in neonates: risk factors and model development
Mingyun Tang1, Xiaofei Ma1, Yuan Gan1
1Department of Neonatology, Guangzhou Wowen and Children's Medical Center, Liuzhou hospital, Liuzhou, 545001, China.
BMC Gastroenterology
|October 11, 2025
Summary
A new predictive model using six indicators can help identify neonates with necrotizing enterocolitis (NEC) who need surgery. This tool aids early decision-making to improve outcomes for critically ill infants.
Area of Science:
- Neonatal surgery
- Pediatric gastroenterology
- Clinical prediction modeling
Background:
- Neonatal necrotizing enterocolitis (NEC) is a critical gastrointestinal emergency in newborns.
- High morbidity and mortality rates underscore the need for timely interventions.
- Early identification of surgical NEC cases is crucial for improving patient outcomes.
Purpose of the Study:
- To identify independent risk factors for surgical NEC.
- To develop a predictive model for surgical intervention in NEC.
- To enhance timely surgical decision-making and improve neonatal prognosis.
Main Methods:
- Retrospective study of 188 neonates with NEC (Bell stage II or higher).
- Comparison between surgical (n=70) and conservative (n=118) treatment groups.
- LASSO and multivariable logistic regression identified risk factors; a nomogram was developed and validated.
Main Results:
- Surgery was required for 37.2% of NEC cases, with significantly higher mortality (17.1% vs. 1.1%).
- Key predictors for surgery included CRP, serum lactate, portal venous gas, reduced intestinal motility, WBC, and absolute lymphocyte count.
- The nomogram achieved high accuracy (AUC=0.946) with excellent discrimination and clinical utility.
Conclusions:
- A nomogram-based predictive model for surgical NEC was developed using six key indicators.
- The model demonstrates high accuracy and clinical utility for predicting surgical needs.
- This tool can assist clinicians in early NEC management, optimizing treatment and reducing mortality.

