主管单位:中华人民共和国
国家卫生健康委员会
主办单位:
总编辑:杨秋
编辑部主任:吴翔宇
邮发代号:80-528
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全年:336.00元
Email:zgyy8888@163.com
电话(传真):010-64428528;
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英文作者:Zou Xiaoling Wang Yonghong Liu Miao
英文单位:Department of Obstetrics the First People′s Hospital of Chenzhou Hunan Province Chenzhou 423000 China
英文关键词:Placentaanterior;Laborinductioninsecondandthirdtrimesterofpregnancy;Riskfactors;Inductionapproach
目的 探究胎盘前置妊娠中晚期经阴道分娩引产失败的危险因素及引产方式的选择。方法 选取湖南省郴州市第一人民医院2016年1月至2021年10月收治的行妊娠中晚期引产的244例胎盘前置孕妇作为研究对象。根据子宫动脉栓塞术(UAE)的应用情况将孕妇分为药物引产组和UAE+药物引产组;根据分娩方式将孕妇分为经阴道分娩组和剖宫产组。收集孕妇的一般资料及引产结局指标,采用多因素Logistic回归模型分析经阴道分娩引产失败的危险因素,构建反向传播神经网络模型并评价其预测效能。结果 244例孕妇中,113例予UAE+药物引产(UAE+药物引产组),131例予药物引产(药物引产组)。202例经阴道分娩(经阴道分娩组),42例行剖宫产分娩(剖宫产组)。经阴道分娩组与剖宫产组年龄≥35岁、引产孕周≥25周、既往剖宫产史比例、胎盘前置程度、胎盘附着位置、胎盘植入、瘢痕子宫、胎儿畸形、死胎及产前反复阴道出血比例比较,差异均有统计学意义(均P<0.05)。多因素Logistic回归分析结果显示,年龄≥35岁、引产孕周≥25周、既往剖宫产史、胎盘附着于前壁、胎盘植入是影响胎盘前置妊娠中晚期引产孕妇经阴道分娩引产失败的独立危险因素,死胎、产前反复阴道出血是保护因素(均P<0.05)。反向传播神经网络模型的受试者工作特征曲线下面积为0.865(95%置信区间:0.817~0.926,P<0.001),校准曲线结果显示该模型预测的准确度较高。UAE+药物引产组的引产时间、发热、胎盘残留比例均长于/高于药物引产组,引产总出血量少于药物引产组[(318±105)ml比(387±116)ml](均P<0.05)。结论 年龄、孕周、既往剖宫产史、胎盘附着位置、胎盘植入、死胎、产前反复阴道出血均与胎盘前置妊娠中晚期孕妇经阴道分娩结局有关,UAE可降低引产总出血量,提高引产安全性。
Objective To explore the risk factors of the failure of vaginal labor induction in second and third trimester of placental previa and the selection of induction approaches. Methods Totally 244 pregnant women with second and third trimester of placenta previa who underwent labor induction in the First People′s Hospital of Chenzhou, Hunan Province from January 2016 to October 2021 were enrolled. According to the application of uterine artery embolization (UAE), they were divided into UAE+drug induction group and drug induction group; according to delivery modes, they were divided into vaginal delivery group and cesarean section group. The general data and induced labor outcome indicators of pregnant women were recorded. Multiveariate Logistic regression model was used to analyze risk factors affecting the failure of vaginal delivery. A back propagation (BP) neural network model was constructed for that and its predictive efficacy was evaluated. Results Among 244 pregnant women, 113 cases underwent UAE+drug induction (UAE+drug induction group) and 131 cases underwent drug induction (drug induction group); 202 cases underwent vaginal delivery (vaginal delivery group) and 42 cases underwent cesarean section (cesarean section group). The differences in rates of age ≥35 years, gestational age for induction ≥25 weeks, previous cesarean section history, degree of placenta previa, placental attachment site, placenta implantation, scar uterus, fetal malformations, stillbirth and repeated prenatal vaginal bleeding were statistically significant between vaginal delivery group and cesarean section group (all P<0.05). Multivariate Logistic regression analysis showed that, age ≥35 years, gestational age for induction ≥25 weeks, previous cesarean section history, placenta attached to the anterior wall, placenta implantation were independent risk factors for the vaginal delivery failure of pregnant women in second and third trimester of placental previa, while stillbirth and repeated prenatal vaginal bleeding were protective factors (all P<0.05). The area under the receiver operating characteristic curve of the BP neural network model was 0.865 (95% confidence interval: 0.817-0.926, P<0.001), and the calibration curve showed that the accuracy of the model prediction is high. The labor induction time, the proportion of fever and placenta residue of the UAE+drug induction group were longer/higher than those of the drug induction group, while the total blood loss during induction was less than that of the drug induction group [(318±105)ml vs (387±116)ml](all P<0.05). Conclusion s Age, gestational age, previous cesarean section history, placental attachment site, placental implantation, stillbirth and repeated prenatal vaginal bleeding are all related to the outcome of vaginal delivery of pregnant women in second and third trimester of placental previa. UAE can reduce the total bleeding and increase the safety of labor induction.
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