Liu Xin, Liu Li-Jun, Jiang Hai-Yan, Zhao Chang-Liang, He Hai-Ying
Department of Neonatology, Third Hospital of Baogang Group, Baotou 014010, China.
Zhongguo Dang Dai Er Ke Za Zhi. 2022 Jul 15;24(7):778-785. doi: 10.7499/j.issn.1008-8830.2202093.
To investigate the risk factors for necrotizing enterocolitis (NEC) in very preterm infants and establish a nomogram model for predicting the risk of NEC.
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 (=77) and non-NEC (=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.
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 (<0.05). The ROC curve of the development set had an area under the curve (AUC) of 0.833 (95%: 0.715-0.952), and the ROC curve of the validation set had an AUC of 0.826 (95%: 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.
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.
探讨极早产儿坏死性小肠结肠炎(NEC)的危险因素,并建立预测NEC风险的列线图模型。
选取2015年1月至2021年12月住院的752例极早产儿作为研究对象,其中2015 - 2020年出生的654例为训练集,2021年出生的98例为验证集。根据是否发生NEC,将训练集分为两组:NEC组(=77例)和非NEC组(=577例)。采用多因素logistic回归分析探讨极早产儿NEC的独立危险因素。使用R软件绘制列线图模型。然后用验证集数据对列线图模型进行验证。采用受试者工作特征(ROC)曲线、Hosmer-Lemeshow拟合优度检验和校准曲线评估列线图模型的性能,用临床决策曲线评估模型的临床实用性。
多因素logistic回归分析显示,新生儿窒息、败血症、休克、低蛋白血症、重度贫血和配方奶喂养是极早产儿发生NEC的独立危险因素(<0.05)。训练集的ROC曲线下面积(AUC)为0.833(95%:0.715 - 0.952),验证集的ROC曲线AUC为0.826(95%:0.797 - 0.862),表明列线图模型具有良好的鉴别能力。校准曲线分析和Hosmer-Lemeshow拟合优度检验显示模型预测值与实际值之间具有良好的准确性和一致性。
新生儿窒息、败血症、休克、低蛋白血症、重度贫血和配方奶喂养是极早产儿发生NEC的独立危险因素。基于多因素logistic回归分析的列线图模型为临床实践中早期评估极早产儿NEC的发生发展提供了一种定量、简单且直观的工具。