摘要
目的分析云南省2016—2017年12家医院新生儿早产的危险因素,并建立新生儿早产的列线图预测模型,为预防新生儿早产发生提供科学依据。方法选取2016—2017年在云南省共12家医院分娩的20445例孕妇,根据是否早产分成早产组1186例和足月组19259例。采用课题组设计的孕妇一般资料调查问卷表对两组孕妇基本情况、孕期信息进行调查登记,通过Logistic回归分析法确定早产的危险因素,利用R软件绘制新生儿早产的列线图预测模型,并检验其预测效能。结果早产组和足月组的双胎及以上分别占9.11%和7.10%,妊高症分别占21.67%和18.57%,妊娠期糖尿病分别占18.21%和15.90%,贫血分别占24.28%和20.70%,胎膜早破分别占11.64%和9.76%,胎盘异常比例分别占7.08%和5.51%,差异均有统计学意义(χ^(2)=6.731,7.055,4.441,8.691,4.437,5.232,P均<0.05);logistic回归分析结果显示,双胎及以上、妊高症、妊娠期糖尿病、贫血、胎膜早破为新生儿早产发生的危险因素(OR=2.378,2.039,1.824,1.825,2.313,P均<0.05);构建预测新生儿早产发生的列线图模型区分度(曲线下面积为0.794,95%CI=0.738~0.850)和精确度(拟合优度HL检验χ^(2)=8.864,P=0.312)均较好。结论基于胎数、妊高症、妊娠期糖尿病、贫血和胎膜早破等5项因素构建的新生儿早产列线图模型可较好地预测新生儿早产的发生,可为预防新生儿早产提供参考。
Objective To analyze the risk factors for neonatal preterm birth in 12 hospitals in Yunnan Province from 2016 to 2017,and to establish a nomogram prediction model for neonatal preterm birth,providing scientific evidence for the prevention of preterm birth.Methods A total of 20445 pregnant women who gave birth in 12 hospitals in Yunnan Province from 2016 to 2017 were collected and grouped into a preterm group(n=1186)and a full-term group(n=19259)according to whether they had a premature delivery.The general information questionnaire of pregnant women designed by the research team was applied to understand the basic conditions and pregnancy information of the two groups,and the risk factors of preterm birth were determined by logistic regression analysis,R software was applied to draw a nomogram prediction model of neonatal preterm birth,and its predictive performance was tested.Results There were significant differences in the proportions of twins and above(9.11%vs 7.10%),pregnancy-induced hypertension(21.67%vs 18.57%),gestational diabetes mellitus(18.21%vs 15.90%),anemia(24.28%vs 20.70%),premature rupture of membranes(11.64%vs 9.76%),and abnormal placenta(7.08%vs 5.51%)between the preterm group and the full-term group(χ^(2)=6.731,7.055,4.441,8.691,4.437,5.232,all P<0.05);the logistic regression analysis showed that the risk factors for neonatal preterm birth were twins and above(OR=2.378),pregnancy-induced hypertension(OR=2.039),gestational diabetes mellitus(OR=1.824),anemia(OR=1.825),and premature rupture of membranes(OR=2.313)(all P<0.05);the discrimination(area under the curve was 0.794,95%CI=0.738-0.850)and precision(goodness of fit HL test,χ^(2)=8.864,P=0.312)of the nomogram model constructed to predict the occurrence of neonatal preterm birth were both good.Conclusions The nomogram model for preterm birth constructed based on 5 factors including number of fetuses,pregnancy-induced hypertension,gestational diabetes mellitus,anemia and premature rupture of membranes can predict the occurrence of neonatal pr
作者
向梅
李传峰
张红
余卫红
吴玉芹
米弘瑛
舒蕾
雷国斌
赵晓芬
杜琨
和灿林
胡浩
拥李将
李杨方
XIANG Mei;LI Chuan-feng;ZHANG Hong;YU Wei-hong;WU Yu-qin;MI Hong-ying;SHU Lei;LEI Guo-bin;ZHAO Xiao-fen;DU Kun;HE Can-lin;HU Hao;YONG Li-jiang;LI Yang-fang(Department of Pediatrics,Honghe First People's Hospital,Honghe,Yunnan 661199,China;Department of Neonatology and Pediatrics,Qujing Maternal and Child Health Hospital,Qujing,Yunnan 655000,China;Department of Neonatology and Pediatrics,Dali Maternal and Child Health Hospital,Dali,Yunnan 650000,China;Department of Neonatology,Wenshan Prefecture People's Hospital,Wenshan,Yunnan 663000,China;Kunming Children's Hospital Special Needs Ward,Kunming,Yunnan,650228;Department of Neonatology,Yunnan First People's Hospital,Kunming,Yunnan 650032,China;Department of Neonatology,Yuxi Children's Hospital,Yuxi,Yunnan 653100,China;Department of Pediatrics,Maitreya First People's Hospital,Mile,Yunnan 652399,China;Department of Neonatology,Kunming Children's Hospital,Kunming,Yunnan 650228,China)
出处
《中国热带医学》
CAS
2023年第6期563-567,共5页
China Tropical Medicine
基金
国家自然科学基金项目(No.82060291)。
关键词
新生儿早产
危险因素
列线图模型
Neonatal preterm birth
risk factors
nomogram model
