Fulminant necrotizing enterocolitis: clinical features and a predictive model

Abstract Background To develop and validate a nomogram model for predicting the risk of fulminant necrotizing enterocolitis (fNEC) in infants with NEC and to summarize the clinical features of fNEC. Methods Neonates admitted to Shengjing Hospital from 1st January 2013 to 31st December 2022 with the...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaoyu Chen, Yuqiao Li, Yuhan Liu, Tianjing Liu, Yongyan Shi
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Pediatrics
Subjects:
Online Access:https://doi.org/10.1186/s12887-025-05902-3
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849235259193819136
author Xiaoyu Chen
Yuqiao Li
Yuhan Liu
Tianjing Liu
Yongyan Shi
author_facet Xiaoyu Chen
Yuqiao Li
Yuhan Liu
Tianjing Liu
Yongyan Shi
author_sort Xiaoyu Chen
collection DOAJ
description Abstract Background To develop and validate a nomogram model for predicting the risk of fulminant necrotizing enterocolitis (fNEC) in infants with NEC and to summarize the clinical features of fNEC. Methods Neonates admitted to Shengjing Hospital from 1st January 2013 to 31st December 2022 with the diagnosis of NEC were randomly divided into a training set or a validation set. Independent risk factors identified by univariate and multivariate logistic regression analyses were used to conduct a nomogram model for fNEC. The model was evaluated by the area under the curve (AUC), calibration curves and decision curve analysis (DCA) in both sets. Results A total of 315 neonates were included, comprising 70 cases of fNEC and 245 cases of non-fulminant NEC. Neonates with fNEC exhibited more severe symptoms, including acidosis, thrombocytopenia, absent bowel sounds, increased need for surgical intervention and significantly higher mortality. The nomogram was developed using four predictors: bloody stool, absence of bowel sounds, elevated lactate levels and pH values. The AUC of the training and validation sets were 0.939 and 0.975, respectively. Calibration curves and the DCA showed satisfactory performance. Conclusions Neonates with fNEC exhibited more severe symptoms. Our nomogram model shows promise in assisting clinicians in predicting fNEC.
format Article
id doaj-art-e3632df3f17740f7aaabbfd14f17dd6d
institution Kabale University
issn 1471-2431
language English
publishDate 2025-07-01
publisher BMC
record_format Article
series BMC Pediatrics
spelling doaj-art-e3632df3f17740f7aaabbfd14f17dd6d2025-08-20T04:02:50ZengBMCBMC Pediatrics1471-24312025-07-012511910.1186/s12887-025-05902-3Fulminant necrotizing enterocolitis: clinical features and a predictive modelXiaoyu Chen0Yuqiao Li1Yuhan Liu2Tianjing Liu3Yongyan Shi4Department of Hematology/Oncology, Children’s Hospital of Soochow UniversityDepartment of Pediatrics, Shengjing Hospital of China Medical UniversityDepartment of Pediatrics, Shengjing Hospital of China Medical UniversityDepartment of Pediatrics, Shengjing Hospital of China Medical UniversityDepartment of Pediatrics, Shengjing Hospital of China Medical UniversityAbstract Background To develop and validate a nomogram model for predicting the risk of fulminant necrotizing enterocolitis (fNEC) in infants with NEC and to summarize the clinical features of fNEC. Methods Neonates admitted to Shengjing Hospital from 1st January 2013 to 31st December 2022 with the diagnosis of NEC were randomly divided into a training set or a validation set. Independent risk factors identified by univariate and multivariate logistic regression analyses were used to conduct a nomogram model for fNEC. The model was evaluated by the area under the curve (AUC), calibration curves and decision curve analysis (DCA) in both sets. Results A total of 315 neonates were included, comprising 70 cases of fNEC and 245 cases of non-fulminant NEC. Neonates with fNEC exhibited more severe symptoms, including acidosis, thrombocytopenia, absent bowel sounds, increased need for surgical intervention and significantly higher mortality. The nomogram was developed using four predictors: bloody stool, absence of bowel sounds, elevated lactate levels and pH values. The AUC of the training and validation sets were 0.939 and 0.975, respectively. Calibration curves and the DCA showed satisfactory performance. Conclusions Neonates with fNEC exhibited more severe symptoms. Our nomogram model shows promise in assisting clinicians in predicting fNEC.https://doi.org/10.1186/s12887-025-05902-3Fulminant necrotizing EnterocolitisPreterm infantsPredictive modelNomogram
spellingShingle Xiaoyu Chen
Yuqiao Li
Yuhan Liu
Tianjing Liu
Yongyan Shi
Fulminant necrotizing enterocolitis: clinical features and a predictive model
BMC Pediatrics
Fulminant necrotizing Enterocolitis
Preterm infants
Predictive model
Nomogram
title Fulminant necrotizing enterocolitis: clinical features and a predictive model
title_full Fulminant necrotizing enterocolitis: clinical features and a predictive model
title_fullStr Fulminant necrotizing enterocolitis: clinical features and a predictive model
title_full_unstemmed Fulminant necrotizing enterocolitis: clinical features and a predictive model
title_short Fulminant necrotizing enterocolitis: clinical features and a predictive model
title_sort fulminant necrotizing enterocolitis clinical features and a predictive model
topic Fulminant necrotizing Enterocolitis
Preterm infants
Predictive model
Nomogram
url https://doi.org/10.1186/s12887-025-05902-3
work_keys_str_mv AT xiaoyuchen fulminantnecrotizingenterocolitisclinicalfeaturesandapredictivemodel
AT yuqiaoli fulminantnecrotizingenterocolitisclinicalfeaturesandapredictivemodel
AT yuhanliu fulminantnecrotizingenterocolitisclinicalfeaturesandapredictivemodel
AT tianjingliu fulminantnecrotizingenterocolitisclinicalfeaturesandapredictivemodel
AT yongyanshi fulminantnecrotizingenterocolitisclinicalfeaturesandapredictivemodel