ISSN 1674-3865  CN 21-1569/R
主管:国家卫生健康委员会
主办:中国医师协会
   辽宁省基础医学研究所
   辽宁中医药大学附属医院

中国中西医结合儿科学 ›› 2025, Vol. 17 ›› Issue (4): 330-335.doi: 10.20274/j.cnki.issn.2025.04.010

• 临床研究 • 上一篇    下一篇

颅内占位性病变患儿术后营养不良风险预测模型的构建及验证研究

李叶(), 宛玉欢, 李卓   

  1. 410007 长沙,中南大学湘雅医学院附属儿童医院(湖南省儿童医院)神经外科
  • 收稿日期:2025-03-27 修回日期:2025-05-13 出版日期:2025-08-25 上线日期:2025-08-25
  • 通讯作者: 李叶 E-mail:TJLY0908@163.com
  • 作者简介:李叶(1988-),女,护师。研究方向:儿科临床护理

Construction and validation of risk prediction model for postoperative malnutrition in children with intracranial space-occupying lesions

Ye LI(), Yuhuan WAN, Zhuo LI   

  1. The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University(Hunan Children's Hospital ), Changsha 410007, China
  • Received:2025-03-27 Revised:2025-05-13 Published:2025-08-25 Online:2025-08-25
  • Contact: Ye LI E-mail:TJLY0908@163.com

摘要:

目的 构建并验证颅内占位性病变患儿术后营养不良风险预测模型,以早期识别高危患儿,制定针对性的营养支持方案,降低术后营养不良的发生率,改善患儿预后。 方法 采用便利抽样法,选取2020年3月至2023年11月在湖南省儿童医院拟行手术治疗的颅内占位性病变患儿167例为研究对象,其中117例作为建模组,50例作为验证组。回顾性收集患儿的一般资料、疾病相关资料、治疗和护理相关资料。通过单因素分析和Logistic回归分析构建风险预测模型,并绘制列线图。使用受试者工作特征(ROC)曲线评估模型的预测效能,Hosmer-Lemeshow检验评估模型的拟合效果。 结果 颅内占位性病变患儿术后营养不良发生率为34.13%(57/167)。Logistic回归分析显示,术前营养不良风险、术后是否出现并发症、围手术期是否接受营养支持、小儿危重病例评分、贫血、血清白蛋白水平和C反应蛋白水平是术后营养不良的独立影响因素(P<0.05)。构建的风险预测模型在建模组的ROC曲线下面积为0.863(95%CI:0.789~0.906),Hosmer-Lemeshow检验P=0.679,拟合效果良好。在验证组中,模型的ROC曲线下面积为0.876(95%CI:0.823~0.927),敏感度为0.735,特异度为0.768,验证结果良好。 结论 本研究构建的颅内占位性病变患儿术后营养不良风险预测模型具有良好的预测效能和拟合效果,可为医护人员早期识别高危患儿、制定个性化营养支持方案提供参考依据,有助于降低术后营养不良的发生率,改善患儿预后。

关键词: 颅内占位, 营养不良, 预测模型, 儿童

Abstract:

Objective To construct and validate a risk prediction model for postoperative malnutrition in children with intracranial space-occupying lesions, in order to identify high-risk children at an early stage, formulate targeted nutritional support plans, reduce the incidence of postoperative malnutrition, and improve the prognosis of children. Methods By using the convenience sampling method, 167 children with intracranial space-occupying lesions who were scheduled to undergo surgical treatment at Hunan Children's Hospital from March 2020 to November 2023 were selected as the research subjects. Among them, 117 cases were taken as the modeling group and 50 cases as the validation group. The general information of the child patients, disease-related information, and information related to treatment and nursing were retrospectively collected. A risk prediction model was constructed through single-factor analysis and Logistic regression analysis, and a nomogram was drawn. The predictive efficacy of the model was evaluated using the receiver operating characteristic (ROC) curve, and the fitting effect of the model was evaluated using the Hosmer-Lemeshow test. Results The incidence of postoperative malnutrition in children with intracranial space-occupying lesions was 34.13%(57/167). Logistic regression analysis showed that preoperative risk of malnutrition, whether complications occurred after surgery, whether nutritional support was received during the perioperative period, pediatric critical illness score, anemia, serum albumin level and C-reactive protein level were independent influencing factors of postoperative malnutrition (P<0.05). The area under the ROC curve of the constructed risk prediction model in the modeling group was 0.863 (95%CI: 0.789-0.906), and the Hosmer-Lemeshow test P=0.679, indicating a good fitting effect. In the validation group, the area under the ROC curve of the model was 0.876 (95%CI: 0.823-0.927), the sensitivity was 0.735, and the specificity was 0.768. The validation results were good. Conclusion The risk prediction model for postoperative malnutrition in children with intracranial space-occupying lesions constructed in this study has good predictive efficacy and fitting effect. It can provide a reference basis for medical staff to identify high-risk children at an early stage and formulate personalized nutritional support plans, which is helpful to reduce the incidence of postoperative malnutrition and improve the prognosis of children.

Key words: Intracranial space occupation, Malnutrition, Prediction model, Child

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