早产风险预测模型研究  

Construction of a prediction model for preterm birth risk

作　　者：汪琼 陈丹青[2] 魏伊丽 钱芳芳 WANG Qiong;CHEN Danqing;WEI Yili;QIAN Fangfang(Zhejiang University School of Medicine,Hangzhou,Zhejiang 310000,China;Obstetrics and Gynecology Hospital,Zhejiang University School of Medicine,Hangzhou,Zhejiang 310000,China)

机构地区：[1]浙江大学医学院,浙江杭州310000 [2]浙江大学医学院附属妇产科医院,浙江杭州310000

出　　处：《预防医学》2024年第8期663-668,共6页China Preventive Medicine Journal

摘　　要：目的构建早产风险预测模型,筛选早产高危人群,预防早产。方法选择2019年1月1日—12月31日在浙江大学医学院附属妇产科医院产检并分娩的孕妇为研究对象,其中80%纳入建模组,20%纳入验证组,收集人口学信息和临床信息。采用多因素logistic回归模型分析建模组早产风险预测因子,根据预测因子的OR值建立早产风险预测模型;以验证组数据验证模型,采用约登指数最大值筛选模型临界值,采用受试者操作特征(ROC)曲线评估模型的预测效果。结果调查孕妇15197人,其中建模组12131人,验证组3066人,两组孕妇的年龄、文化程度和孕次等资料差异无统计学意义(均P<0.05)。多因素logistic回归模型分析结果显示,孕次、文化程度、居住地、高血压、糖尿病、早产史、双胎妊娠、前置胎盘和妊娠高血压是早产的风险预测因子。孕次>2次为2分,高中及以下学历为4分,大专/本科以上学历为-4分,居住在农村为5分,高血压为7分,糖尿病为11分,有早产史为11分,双胎妊娠为28分,前置胎盘为19分,妊娠高血压为12分,该模型总分值范围为-4~99分。该模型临界值8分,约登指数最大,为0.480,曲线下面积为0.749(95%CI:0.732~0.767),灵敏度和特度分别为0.610和0.886,提示该模型预测效果良好。结论本研究基于孕妇人口学和临床特征建立的早产风险预测模型可较好地预测孕妇早产的风险。Objective To construct a prediction model for preterm birth risk among pregnant women,so as to provide the reference for screening high-risk population and preventing preterm birth.Methods Pregnant women who received antenatal examination and delivered at the Women's Hospital,School of Medicine,Zhejiang University from January 1 to December 31,2019 were selected as the study subjects,among them,80%were included in the modeling group,and 20%were included in the validation group.Demographic and clinical information were collected.A multivariable logistic regression model was used to analyze the predictive factors of preterm birth risk in the modeling group,and a preterm birth risk prediction model was established based on the OR values of predictive factors.The model was validated with the data from the validation group.The Youden index was used to determine the critical score for predicting preterm birth risk.The prediction performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results A total of 15197 pregnant women were surveyed,including 12131 pregnant women in the observation group and 3066 pregnant women in the validation group.There was no statistically significant difference in age,education level and gravidity between the two groups of pregnant women(all P<0.05).Multivariable logistic regression analysis identified the number of pregnancies,education level,place of residence,hypertension,diabetes,history of preterm birth,twin-pregnancy,placenta praevia,and gestational hypertension as risk prediction factors for preterm birth risk among pregnant women.The risk score system for preterm birth was established as follows:>2 pregnancies(2 points),high school education or below(4 points),college degree or above(-4 points),rural residence(5 points),hypertension(7 points),diabetes(11 points),history of preterm birth(11 points),twin-pregnancy(28 points),placenta previa(19 points),and gestational hypertension(12 points).The total score of the preterm birth risk scoring system ran

关 键 词：早产 预测模型 人口学特征 临床特征 

分 类 号：R714[医药卫生—妇产科学]