Establishment of a nomogram model for predicting necrotizing enterocolitis in very preterm infants.
10.7499/j.issn.1008-8830.2202093
- Author:
Xin LIU
1
;
Li-Jun LIU
1
;
Hai-Yan JIANG
1
;
Chang-Liang ZHAO
1
;
Hai-Ying HE
1
Author Information
1. Department of Neonatology, Third Hospital of Baogang Group, Baotou 014010, China.
- Publication Type:Journal Article
- Keywords:
Necrotizing enterocolitis;
Nomogram;
Risk factor;
Very preterm infant
- MeSH:
Asphyxia/complications*;
Child;
Enterocolitis, Necrotizing/etiology*;
Female;
Fetal Growth Retardation;
Humans;
Hypoalbuminemia;
Infant;
Infant, Newborn;
Infant, Newborn, Diseases;
Infant, Premature;
Infant, Premature, Diseases/etiology*;
Nomograms;
Sepsis/complications*
- From:
Chinese Journal of Contemporary Pediatrics
2022;24(7):778-785
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVES:To investigate the risk factors for necrotizing enterocolitis (NEC) in very preterm infants and establish a nomogram model for predicting the risk of NEC.
METHODS:A total of 752 very preterm infants who were hospitalized from January 2015 to December 2021 were enrolled as subjects, among whom 654 were born in 2015-2020 (development set) and 98 were born in 2021 (validation set). According to the presence or absence of NEC, the development set was divided into two groups: NEC (n=77) and non-NEC (n=577). A multivariate logistic regression analysis was used to investigate the independent risk factors for NEC in very preterm infants. R software was used to plot the nomogram model. The nomogram model was then validated by the data of the validation set. The receiver operating characteristic (ROC) curve, the Hosmer-Lemeshow goodness-of-fit test, and the calibration curve were used to evaluate the performance of the nomogram model, and the clinical decision curve was used to assess the clinical practicability of the model.
RESULTS:The multivariate logistic regression analysis showed that neonatal asphyxia, sepsis, shock, hypoalbuminemia, severe anemia, and formula feeding were independent risk factors for NEC in very preterm infants (P<0.05). The ROC curve of the development set had an area under the curve (AUC) of 0.833 (95%CI: 0.715-0.952), and the ROC curve of the validation set had an AUC of 0.826 (95%CI: 0.797-0.862), suggesting that the nomogram model had a good discriminatory ability. The calibration curve analysis and the Hosmer-Lemeshow goodness-of-fit test showed good accuracy and consistency between the predicted value of the model and the actual value.
CONCLUSIONS:Neonatal asphyxia, sepsis, shock, hypoalbuminemia, severe anemia, and formula feeding are independent risk factors for NEC in very preterm infant. The nomogram model based on the multivariate logistic regression analysis provides a quantitative, simple, and intuitive tool for early assessment of the development of NEC in very preterm infants in clinical practice.
