Shi Bo, Shen Leiting, Huang Wenchang, Cai Linghao, Yang Sisi, Zhang Yuanyuan, Tou Jinfa, Lai Dengming
Department of Neonatal Surgery, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China.
Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China.
J Clin Med. 2023 Apr 23;12(9):3062. doi: 10.3390/jcm12093062.
To explore the surgical risk variables in patients with necrotizing enterocolitis (NEC) and develop a nomogram model for predicting the surgical intervention timing of NEC.
Infants diagnosed with NEC were enrolled in our study. We gathered information from clinical data, laboratory examinations, and radiological manifestations. Using LASSO (least absolute shrinkage and selection operator) regression analysis and multivariate logistic regression analysis, a clinical prediction model based on the logistic nomogram was developed. The performance of the nomogram model was evaluated using the receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA).
A surgical intervention risk nomogram based on hypothermia, absent bowel sounds, WBC > 20 × 10/L or < 5 × 10/L, CRP > 50 mg/L, pneumatosis intestinalis, and ascites was practical, had a moderate predictive value (AUC > 0.8), improved calibration, and enhanced clinical benefit.
This simple and reliable clinical prediction nomogram model can help physicians evaluate children with NEC in a fast and effective manner, enabling the early identification and diagnosis of children at risk for surgery. It offers clinical revolutionary value for the development of medical or surgical treatment plans for children with NEC.
探讨坏死性小肠结肠炎(NEC)患者的手术风险变量,并建立一个用于预测NEC手术干预时机的列线图模型。
将诊断为NEC的婴儿纳入本研究。我们从临床数据、实验室检查和影像学表现中收集信息。使用LASSO(最小绝对收缩和选择算子)回归分析和多因素逻辑回归分析,建立了基于逻辑列线图的临床预测模型。使用受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)对列线图模型的性能进行评估。
基于体温过低、肠鸣音消失、白细胞>20×10⁹/L或<5×10⁹/L、C反应蛋白>50mg/L、肠壁积气和腹水建立的手术干预风险列线图实用,具有中等预测价值(AUC>0.8),改善了校准,并提高了临床效益。
这种简单可靠的临床预测列线图模型可以帮助医生快速有效地评估NEC患儿,能够早期识别和诊断有手术风险的儿童。它为制定NEC患儿的医疗或手术治疗方案提供了临床变革价值。