摘要
目的基于临床特征构建个体化预测妊娠期肝内胆汁淤积症(ICP)患者并发胎儿生长受限的Nomogram模型,并进行效能验证。方法采用回顾性分析,选取山东第一医科大学附属济南妇幼保健院2018年1月至2024年1月收治的344例ICP患者临床资料,随访至分娩,根据是否并发胎儿生长受限分为发生组、未发生组,对比两组临床资料。采用独立样本t检验、χ^(2)检验进行统计比较,多因素logistic回归分析ICP并发胎儿生长受限的影响因素;应用R软件构建个体化预测Nomogram模型,绘制受试者操作特征曲线(ROC)和校准曲线验证模型的预测效能。结果344例ICP患者中,并发胎儿生长受限51例,发生率为14.83%。发生组妊娠期高血压综合征占比、妊娠期糖尿病占比和总胆汁酸水平均高于未发生组(均P<0.05),羊水指数、叶酸水平均低于未发生组(均P<0.05);妊娠期高血压综合征(OR=2.675,95%CI:1.382~5.179)、妊娠期糖尿病(OR=2.921,95%CI:1.494~5.711)、总胆汁酸(OR=1.956,95%CI:1.089~3.515)、羊水指数(OR=0.471,95%CI:0.285~0.780)、叶酸(OR=0.525,95%CI:0.322~0.856)是ICP患者并发胎儿生长受限的影响因素(均P<0.05);将影响因素作为风险预测因子构建ICP并发胎儿生长受限的个体化预测Nomogram模型,经ROC验证显示其预测ICP并发胎儿生长受限的曲线下面积、灵敏度、特异度依次为0.932(95%CI:0.869~0.970)、94.12%、85.67%,校准曲线显示模型预测概率和实际概率相近,经Hosmer-Lemeshow拟合优度检验显示拟合良好(χ^(2)=1.905,P=0.312)。结论妊娠期高血压综合征、妊娠期糖尿病、总胆汁酸、羊水指数、叶酸是ICP患者并发胎儿生长受限的影响因素,基于上述临床特征构建的个体化预测Nomogram模型对ICP并发胎儿生长受限的预测效能佳,有良好的临床应用价值。
Objective To construct a Nomogram model to predict fetal growth restriction in patients with intrahepatic cholestasis of pregnancy(ICP)based on the clinical features,and to verify its efficacy.Methods The clinical data of 344 patients with ICP treated at Jinan Maternal and Child Health Hospital Affiliated to Shandong First Medical University from January 2018 to January 2024 were retrospectively analyzed.They were followed up until delivery.They were divided into an occurrence group and a non-occurrence group according to whether they had fetal growth restriction,and the clinical data were compared between the two groups by independent-sample t test andχ^(2)test.The influencing factors of ICP complicated with fetal growth restriction were analyzed by the multivariate logistic regression analysis.The individualized prediction Nomogram model was constructed using the R software,and receiver operating characteristic curves(ROC)and calibration curves were drawn to verify the prediction efficacy of the model.Results Among the 344 patients,51 had fetal growth restriction,with an incidence rate of 14.83%.The proportions of the patients with pregnancy-induced hypertension syndrome and gestational diabetes mellitus and the level of total bile acid in the occurrence group were higher than those in the non-occurrence group(all P<0.05),and the amniotic fluid index and folic acid level were lower(both P<0.05).Pregnancy-induced hypertension syndrome(OR=2.675,95%CI 1.382-5.179),gestational diabetes mellitus(OR=2.921,95%CI 1.494-5.711),total bile acid(OR=1.956,95%CI 1.089-3.515),amniotic fluid index(OR=0.471,95%CI 0.285-0.780),and folic acid(OR=0.525,95%CI 0.322-0.856)were the influencing factors of fetal growth restriction in the patients(all P<0.05).Taking the influencing factors as risk predictors,an individualized prediction Nomogram model for fetal growth restriction in the patients was constructed.The ROC showed that the area under the curve,sensitivity,and specificity for predicting fetal growth restriction in the patients with ICP were 0.932(95%CI 0.869-0.970),94.12%,and 85.67%,respectively;the calibration curve showed that the prediction probability of the model was close to the actual probability;the Hosmer-Lemeshow goodness-of-fit test showed that the fitting was good(χ^(2)=1.905,P=0.312).Conclusions Pregnancy-induced hypertension syndrome,gestational diabetes mellitus,total bile acid,amniotic fluid index,and folic acid are the influencing factors of fetal growth restriction in patients with ICP.The individualized prediction Nomogram model based on the above clinical features has good prediction efficacy for ICP complicated with fetal growth restriction and good clinical application value.
作者
王晓丽
李杰
王步非
罗丽梅
Wang Xiaoli;Li Jie;Wang Bufei;Luo Limei(Department of Obstetrics,Jinan Maternal and Child Health Hospital Affiliated to Shandong First Medical University,Jinan 250001,China;Department of Obstetrics,Shandong Maternal and Child Health Hospital,Jinan,250000,China)
出处
《国际医药卫生导报》
2025年第14期2341-2346,共6页
International Medicine and Health Guidance News
基金
山东省卫生健康政策研究重点课题(WZY202249)。
关键词
胎儿生长受限
妊娠期肝内胆汁淤积症
影响因素
临床特征
预测价值
Fetal growth restriction
Intrahepatic cholestasis of pregnancy
Influencing factors
Clinical features
Predictive value
