Development and Validation of a Nomogram for Predicting the Risk of Bell's Stage II/III Necrotizing Enterocolitis in Neonates Compared to Bell's Stage I

Front Pediatr. 2022 Jun 14:10:863719. doi: 10.3389/fped.2022.863719. eCollection 2022.

Abstract

Background: Patients with Bell's Stage II/III necrotizing enterocolitis (NEC) may have more severe presentations, higher rates of death, and more long-term complications than those with Bell's Stage I NEC, so the purpose of this article was to construct a nomogram model to distinguish Bell's stage II/III NEC early from Bell's Stage I NEC, which is critical in the clinical management of NEC.

Patients and methods: A total of 730 NEC newborns diagnosed from January 2015 to January 2021 were retrospectively studied. They were randomly divided into training and validation groups at the ratio of 7:3. A nomogram model for predicting NEC was developed based on all the independent risk factors by multivariate regression analysis. The model's performance was mainly evaluated through three aspects: the area under the curve (AUC) to verify discrimination, the Hosmer-Lemeshow test and calibration curve to validate the consistency, and decision curve analysis (DCA) to determine the clinical effectiveness.

Results: Predictors included in the prediction model were gestational age (GA), birth weight (BW), asphyxia, septicemia, hypoglycemia, and patent ductus arteriosus (PDA). This nomogram model containing the above-mentioned six risk factors had good discrimination ability in both groups, and the AUCs were 0.853 (95% CI, 0.82-0.89) and 0.846 (95% CI, 0.79-0.90), respectively. The calibration curve and DCA confirmed that the nomogram had good consistency and clinical usefulness.

Conclusions: This individual prediction nomogram based on GA, BW, asphyxia, septicemia, hypoglycemia, and PDA served as a useful tool to risk-stratify patients with NEC, and can help neonatologists early distinguish Bell's stage II/III NEC early from Bell's Stage I NEC.

Keywords: necrotizing enterocolitis; neonate; nomogram; prediction model; risk factors.