Shenzhen Children's Hospital, Shenzhen, China.
Pediatr Surg Int. 2024 Nov 30;41(1):14. doi: 10.1007/s00383-024-05916-5.
The aim of this study was to develop and validate an intestinal stenosis prediction model for postoperative newborns with neonatal necrotizing enterocolitis (NEC).
Clinical information was collected on neonates who had undergone anastomosis or enterostomy because of NEC. The least absolute shrinkage and selection operator regression was applied to identify risk factors included in the model for postoperative intestinal stenosis. Multivariate logistic regression analysis was used to develop a predicting model regression based on the selected variables. Then internal validation was assessed using the bootstrapping validation. The accuracy and applicability of the model are assessed by C-index, calibration and decision curve.
Predictors incorporated into the model were a weight on admission, hematochezia, duration of abnormal C-reactive protein, lactate, intestinal peristalsis vanish, operation methods and duration of surgery. The regression equation was logit (P) = -0.001X + 1.566X + 0.185X + 0.304X + 1.34X - 2.932X + 0.015X - 3.193, where X was weight on admission (g), X was hematochezia (yes = 1, no = 0), X was duration of abnormal C-reactive protein (days), X was lactate (mmol/L), X was intestinal peristalsis vanish (yes = 1, no = 0), X was primary anastomosis (yes = 1, no = 0), X was duration of surgery (min). The model displayed good discrimination with a C-index of 0.879 (0.827,0.932) by random sampling for 1000 times. The calibration curve excluded the overfitting performance, and the decision curve confirmed the clinical application capacity of the model.
This nomogram of intestinal stenosis incorporating the use of weight on admission, hematochezia, duration of abnormal C-reactive protein, lactate, intestinal peristalsis vanish, operation methods and duration of surgery could be conveniently used to facilitate the intestinal stenosis risk prediction in postoperative-NEC-patients.
本研究旨在建立并验证一种用于预测新生儿坏死性小肠结肠炎(NEC)术后新生儿发生肠狭窄的模型。
收集因 NEC 而行吻合术或肠造口术的新生儿的临床资料。应用最小绝对收缩和选择算子回归来确定纳入模型的术后肠狭窄风险因素。采用多变量逻辑回归分析,基于所选变量建立预测模型回归。然后采用自举验证法对内部分类进行验证。通过 C 指数、校准和决策曲线评估模型的准确性和适用性。
纳入模型的预测因子为入院体重、血便、异常 C 反应蛋白持续时间、乳酸、肠蠕动消失、手术方法和手术持续时间。回归方程为 logit(P)= -0.001X + 1.566X + 0.185X + 0.304X + 1.34X - 2.932X + 0.015X - 3.193,其中 X 为入院体重(g),X 为血便(是=1,否=0),X 为异常 C 反应蛋白持续时间(天),X 为乳酸(mmol/L),X 为肠蠕动消失(是=1,否=0),X 为一期吻合(是=1,否=0),X 为手术持续时间(min)。通过随机抽样 1000 次,该模型的 C 指数为 0.879(0.827,0.932),具有良好的区分度。校准曲线排除了过拟合表现,决策曲线证实了该模型的临床应用能力。
本研究建立的基于入院体重、血便、异常 C 反应蛋白持续时间、乳酸、肠蠕动消失、手术方法和手术持续时间的肠狭窄预测模型,可方便用于预测术后 NEC 患儿发生肠狭窄的风险。