多因素综合构建妊娠期糖尿病孕妇分娩巨大儿的预测模型

    Construction of the prediction model of macrosomia in pregnant women with gestational diabetes mellitus

    • 摘要:
      目的多因素综合构建妊娠期糖尿病孕妇分娩巨大儿的预测模型。
      方法选取妊娠期糖尿病孕妇120例,根据新生儿出生体质量不同分为巨大儿组(n=33)和正常组(n=87)。收集2组一般临床资料,采用logistic回归分析构建妊娠期糖尿病孕妇分娩巨大儿的预测模型,并绘制ROC曲线。
      结果2组孕妇孕期增重、孕前体质量指数、分娩孕周、空腹血糖、口服糖耐量试验0 h血糖及胰岛素抵抗指数差异均有统计学意义(P < 0.01);logistic回归分析显示,孕期增重、空腹血糖、胰岛素抵抗指数均为妊娠期糖尿病孕妇分娩巨大儿的独立危险因素(P < 0.05)。将孕期增重、空腹血糖、胰岛素抵抗指数分别作为协变量X1X2X3,得出预测模型表达式为:Logit(P)=-10.522+0.521X1+0.337X2+0.216X3,该模型最佳临界值为0.522,灵敏度为73.68%,特异度为93.90%,ROC曲线下面积为0.856(0.614~0.977)。
      结论多因素综合构建预测模型对妊娠期糖尿病孕妇分娩巨大儿具有较好预测价值。

       

      Abstract:
      ObjectiveTo construct the prediction model of macrosomia in pregnant women with gestational diabetes mellitus.
      MethodsOne hundred and twenty pregnant women with gestational diabetes mellitus were divided into the macrosomia group(n=33) and normal group(n=87) according to the different birth body mass of newborns.The general clinical data of two groups were collected, the logistic regression was used to construct the prediction model of macrosomia in pregnant women with gestational diabetes mellitus, and the receiver operating characteristic(ROC) curve of subjects was drawn.
      ResultsThe differences of the weight gain during pregnancy, pre-pregnancy body mass index, gestational age, fasting blood glucose, OGTT 0 h blood glucose and insulin resistance index between two groups were statistically significant(P < 0.01).The results of logistic regression analysis showed that the weight gain during pregnancy, fasting blood glucose, insulin resistance index were the independent risk factors of the delivery of macrosomia(P < 0.05).The weight gain during pregnancy, fasting blood glucose and insulin resistance index were taken as covariates X1, X2 and X3, respectively, and the prediction model expression was obtained as follows: Logit(P)=-10.522+0.521X1+0.337X2+0.216X3.The optimal critical value, sensitivity, specificity and area under the ROC curve of model were 0.522, 73.68%, 93.90% and 0.856(0.614-0.977), respectively.
      ConclusionsThe prediction model based on multiple factors has a high value in the prediction of macrosomia of pregnant women with gestational diabetes mellitus.

       

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