Chen Yixian, Duan Yuhui, Wei Ba, Jiang Yongjiang, Tan Yadan, Wei Yijun, Gan Yuan, Chen Yujun
Department of Pediatrics, The Second Affiliated Hospital of Guangxi Medical University, Guangxi, China.
Neonatology, Liuzhou Hospital of Guangzhou Women and Children's Medical Center, Guangxi, China.
Pediatr Res. 2025 Apr;97(5):1636-1643. doi: 10.1038/s41390-024-03605-6. Epub 2024 Sep 28.
Whether portal venous gas (PVG) is a sign of severe neonatal necrotizing enterocolitis (NEC) and predicts poor prognosis remains uncertain.
Patients from two centres were randomly assigned to a training set or a validation set. A nomogram model for predicting severe NEC was developed on the basis of the independent risk factors selected by least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis. The model was evaluated based on the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).
A total of 585 patients met the study criteria, and propensity score matching resulted in 141 matched pairs for further analysis. Patients with PVG had a greater risk of surgical intervention or death compared with patients without PVG. A prediction model for severe NEC was established based on PVG, invasive mechanical ventilation (IMV), serum platelet count (PLT) and pH <7.35 at the onset of NEC. The model had a moderate predictive value with an AUC > 0.8. The calibration curve and DCA suggested that the nomogram model had good performance for clinical application.
A prediction nomogram model based on PVG and other risk factors can help physicians identify severe NEC early and develop reasonable treatment plans.
PVG is an important and common imaging manifestation of NEC. Controversy exists regarding whether PVG is an indication for surgical intervention and predicts poor prognosis. Our study suggested that patients with PVG had a greater risk of surgical intervention or death compared with patients without PVG. PVG, IMV, PLT and pH <7.35 at the onset of NEC are independent risk factors for severe NEC. A prediction nomogram model based on PVG and other risk factors may help physicians identify severe NEC early and develop reasonable treatment plans.
门静脉气体（PVG）是否为严重新生儿坏死性小肠结肠炎（NEC）的征象以及是否预示预后不良仍不确定。
来自两个中心的患者被随机分配到训练集或验证集。基于通过最小绝对收缩和选择算子（LASSO）回归分析及多因素逻辑回归分析所选择的独立危险因素，开发了一种预测严重NEC的列线图模型。基于曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）对该模型进行评估。
共有585例患者符合研究标准，倾向得分匹配产生141对匹配对用于进一步分析。与无PVG的患者相比，有PVG的患者接受手术干预或死亡的风险更高。基于PVG、有创机械通气（IMV）、血清血小板计数（PLT）以及NEC发病时pH<7.35建立了严重NEC的预测模型。该模型具有中等预测价值，AUC>0.8。校准曲线和DCA表明列线图模型在临床应用中具有良好性能。
基于PVG和其他危险因素的预测列线图模型可帮助医生早期识别严重NEC并制定合理的治疗方案。
PVG是NEC重要且常见的影像学表现。关于PVG是否为手术干预指征及是否预示预后不良存在争议。我们的研究表明，与无PVG的患者相比，有PVG的患者接受手术干预或死亡的风险更高。PVG、IMV、PLT以及NEC发病时pH<7.35是严重NEC的独立危险因素。基于PVG和其他危险因素的预测列线图模型可能有助于医生早期识别严重NEC并制定合理的治疗方案。
