人民卫生出版社系列期刊
ISSN 2096-2738 CN 11-9370/R

中国科技核心期刊(中国科技论文统计源期刊)
2020《中国学术期刊影响因子年报》统计源期刊

新发传染病电子杂志 ›› 2023, Vol. 8 ›› Issue (4): 64-68.doi: 10.19871/j.cnki.xfcrbzz.2023.04.014

• 论著 • 上一篇    下一篇

妊娠晚期孕妇生殖道感染的危险因素及其与早产的相关性分析

王瑞, 李文华, 唐丽文   

  1. 佛山市南海区人民医院产科,广东 佛山 528200
  • 收稿日期:2023-02-11 出版日期:2023-08-31 发布日期:2023-09-26
  • 通讯作者: 王瑞,Email:zicain51593@163.com

Analysis of the risk factors of reproductive tract infections of pregnant women in the third trimester of pregnancy and their correlation with preterm delivery

Wang Rui, Li Wenhua, Tang Liwen   

  1. Department of Obstetrics, Nanhai District People's Hospital in Foshan City, Guangdong Foshan 528200, China
  • Received:2023-02-11 Online:2023-08-31 Published:2023-09-26

摘要: 目的 探讨妊娠晚期孕妇生殖道感染的危险因素及生殖道感染与早产发生的关系。方法 选取2018年2月至2020年1月于佛山市南海区人民医院产科就诊的妊娠晚期孕妇123例,依据孕妇是否患有生殖道感染分为感染组(n=49)和对照组(n=74),比较两组患者的临床数据,采用多因素Logistic回归分析妊娠晚期孕妇生殖道感染的独立危险因素。根据是否早产将123例产妇分为早产组(n=35)和非早产组(n=88),对比两组产妇一般资料,采用多因素Logistic回归分析妊娠晚期孕妇早产的独立危险因素。依据独立因素构建预测模型,通过Bootstrap自抽样法进行验证。结果 妊娠期糖尿病、高中及以下学历、不良卫生习惯、流产史、分娩史、生殖道感染史是妊娠晚期孕妇生殖道感染的独立危险因素(P<0.05)。对比不同孕龄早产儿出生时及出生后情况可知,胎龄越小、出生体重越低,其窒息、肺透明膜病、Ul度以上脑室内出血发病率及死亡发生率越高(P<0.05)。妊娠期糖尿病、流产史、生殖道感染是妊娠晚期孕妇早产的独立危险因素(P<0.05)。构建妊娠晚期孕妇早产预测模型,该预测模型C-index计算结果为0.863(95%CI:0.825~0.884),ROC曲线AUC为0.868(95%CI:0.822~0.963),具有良好的区分度和准确性。结论 妊娠期糖尿病、高中及以下学历、不良卫生习惯、流产史、分娩史、生殖道感染史是妊娠晚期孕妇生殖道感染的危险因素,增强产妇的安全意识,及时清洁生殖道并定期进行相关检查,减少非必要的流产和剖宫产,可以有效降低生殖道感染的风险和早产率。

关键词: 妊娠晚期, 孕妇, 生殖道感染, 早产

Abstract: Objective Explore the relevant influencing factors of reproductive tract infections in late pregnancy women, and the relationship between reproductive tract infections and premature birth. Method 123 late pregnancy women who were treated at the Department of Obstetrics, Nanhai District People's Hospital in Foshan City from February 2018 to January 2020 were selected. They were divided into an infection group (n=49) and a control group (n=74) based on whether they had reproductive tract infections. The clinical data of the two groups of patients were compared, and Logistic regression analysis was used to analyze the independent risk factors of reproductive tract infections in late pregnancy women. 123 pregnant women were divided into preterm delivery group (n=35) and non preterm delivery group (n=88) based on whether they were born prematurely. The general information of the two groups of pregnant women was compared, and Logistic regression analysis was used to analyze the independent risk factors for preterm delivery in late pregnancy pregnant women. Build a prediction model based on independent factors and validate the model. Result Diabetes in pregnancy, low education level, poor health habits, abortion history, delivery history, infection history were independent risk factors of reproductive tract infection in late pregnancy (P<0.05). By comparing the conditions of preterm infants of different gestational ages at birth and after birth, we can see that the smaller the gestational age and the lower the birth weight, the higher the incidence rate and death rate of asphyxia, hyaline membrane disease, and intraventricular hemorrhage above Ul degree (P<0.05). Pregnancy diabetes, abortion history and reproductive tract infection were independent risk factors for preterm delivery in late pregnancy (P<0.05). Construct a prediction model for premature delivery in late pregnancy. The C-index calculation result of the prediction model is 0.863 (95% CI: 0.825-0.884), and the ROC curve AUC is 0.868 (95% CI: 0.822-0.963), which has good discrimination and accuracy. Conclusion Diabetes during pregnancy, low education level, poor health habits, abortion history, delivery history, infection history are the risk factors of reproductive tract infection in late pregnancy. Enhance maternal safety awareness, timely cleaning of the reproductive tract and regular relevant examinations, reduce unnecessary abortion and cesarean section, effectively reduce the risk of reproductive tract infection and the rate of preterm birth.

Key words: Late pregnancy, Pregnant women, Reproductive tract infections, Premature delivery

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