内科2024，Vol.19Issue(3)：225-231,7.
基于中孕期临床数据构建孕妇发生自发性早产的预测模型:一项单中心的回顾性研究
A prediction model for spontaneous preterm birth in pregnant women based on clinical data in the second trimester of pregnancy:a single-center retrospective study
摘要
Abstract
Objective To analyze influencing factors for spontaneous preterm birth(SPB)in pregnant women based on the clinical data in the second trimester of pregnancy,according to which to build a prediction model.Methods The clinical data of 1,051 pregnant women were retrospectively analyzed,among them,pregnant women who delivered at gestational week＜37 were the SPB group,and pregnant women who delivered at gestational week ≥37 were the full-term group.The multivariate logistic regression model was used to explore influencing factors for SPB in pregnant women.Pregnant women were randomly divided into the training set and the validation set in a ratio of 7:3.The decision tree algorithm was used to establish a prediction model for SPB in pregnant women,whose performance was evaluated by the receiver operating characteristic(ROC)curve.Results The results of multivariate analysis showed that the age at the delivery(OR=1.070,95％CI:1.001～1.144)and times of pregnancy(OR=1.888,95％CI:1.023～3.485),as well as white blood cell count(OR=1.144,95％CI:1.026～1.276),neutrophil-to-lymphocyte ratio(NLR)(OR=1.603,95％CI:1.152～2.232),fetal fibronectin(fFN)(OR=6.961,95％CI:3.740～12.955),and vaginal clearing degree(OR=6.673,95％CI:3.661～12.161)in the second trimester of pregnancy,were influencing factors for SPB in pregnant women(all P＜0.05).The areas under the ROC curves of the decision tree model in the training set and validation set were 0.796(95％CI:0.720～0.871)and 0.786(95％CI:0.658～0.913),respectively,and the accuracy rates were 93.99％and 94.83％,respectively.The Delong test results showed that there was no statistically significant difference in the area under the ROC curve between the decision tree models in the training set and the validation set(D=0.126,P=0.786),which indicated that the model had a good prediction performance.Conclusion Age at the delivery and times of pregnancy,as well as white blood cell count,NLR level,fFN,and vaginal clearing degree in the second trimester of pregnancy,are influencing factors for the occurrence of SPB in pregnant women,and the decision tree model based on these factors has a good prediction performance,which can provide a reference for the personalized prediction for the risk of SPB in pregnant women.关键词
早产/孕中期/影响因素/中性粒细胞与淋巴细胞比值/决策树/预测/模型Key words
Preterm birth/Second trimester of pregnancy/Influencing factor/Neutrophil-to-lymphocyte ratio/Decision tree/Prediction/Model分类
医药卫生引用本文复制引用
黄晶,宁思婷,孔琳..基于中孕期临床数据构建孕妇发生自发性早产的预测模型:一项单中心的回顾性研究[J].内科,2024,19(3):225-231,7.基金项目
广西壮族自治区卫生健康委员会自筹经费科研课题(Z20190068) （Z20190068）
