关键词: 个性化预测, 列线图模型, 坏死性小肠结肠炎, 新生儿

Abstract: Objective To explore the construction of nomogram model for personalized prediction of neonatal necrotizing enterocolitis (NEC) risk,in order to provide scientific reference for the treatment and prevention of neonatal NEC. Methods The clinical data of 1 173 newborns delivered in Hainan Modern Women's and Children's Hospital and the outer hospital from October 2017 to December 2019 were retrospectively collected and analyzed,and were divided into NEC group(n=46) and non-NEC group(n=1 127). Logistic regression model was used to analyze the independent risk factors of NEC. Based on the selected independent risk factors,the nomogram model of NEC risk was constructed by R software,the area under ROC curve was used to test the prediction effect of the model,and the fit goodness was verified. Results The incidence of neonatal NEC was 3.92% (46/1 173). Multivariate Logistic regression analysis showed that gestational age ＜32 weeks(OR=3.186),birth weight ＜1.5 kg (OR=2.250),septic shock(OR=2.517),septicemia(OR=2.566),gestational diabetes mellitus(OR=1.973) and artificial feeding(OR=2.267) were independent risk factors of neonatal NEC(P<0.05),and prenatal use of dexamethasone was a protective factor (OR=0.475,P＜0.05). The area under ROC curve in this prediction model was 0.741. Hosmer-Lemeshow goodness-of-fit test showed good fit (χ²=7.859,P=0.447). The calibration curve of nomogram was a straight line with slope close to 1. Conclusions The nomogram model for personalized predicting the risk of neonatal NEC has good discrimination and accuracy. It can effectively evaluate the occurrence probability of neonatal NEC,and can provide certain guidance value for the prevention and treatment of neonatal NEC.

Key words: personalized prediction, nomogram model, necrotizing enterocolitis, newborns