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医学指征性早期早产引产中阴道分娩的预测因素

Predictors of vaginal delivery in medically indicated early preterm induction of labor.

作者信息

Sievert Rachel A, Kuper Spencer G, Jauk Victoria C, Parrish Melissa, Biggio Joseph R, Harper Lorie M

机构信息

Center for Women's Reproductive Health, University of Alabama at Birmingham, Birmingham, AL.

Center for Women's Reproductive Health, University of Alabama at Birmingham, Birmingham, AL.

出版信息

Am J Obstet Gynecol. 2017 Sep;217(3):375.e1-375.e7. doi: 10.1016/j.ajog.2017.05.025. Epub 2017 May 17.

Abstract

BACKGROUND

When delivery is indicated prior to 34 weeks, many providers perform a cesarean delivery rather than induce labor based on perceptions of a high failure rate. Given the morbidity of cesarean delivery, an accurate estimate of the success rate and factors associated with success in preterm induction of labor is important in management decisions.

OBJECTIVE

We sought to develop a prediction model for successful induction of labor in preterm patients using factors known at the time the decision is made to deliver.

STUDY DESIGN

A retrospective cohort study of all live singletons undergoing an indicated induction of labor between 23 and 34 0/7 weeks from 2011 through 2015. Pregnancies with major fetal anomalies or no intrapartum fetal monitoring were excluded. Successful induction of labor was defined as vaginal delivery. The cohort was randomly split into a training cohort to develop a prediction model for vaginal delivery and a validation cohort to test the model. Factors significantly associated with vaginal delivery were identified using univariate analyses, and candidate factors were used in the multivariate logistic regression model. Only factors known at the start of the induction of labor were used in the model. Receiver-operating characteristic curves were created to estimate the predictive value of the model. Sensitivity and specificity of the model were assessed.

RESULTS

Of 331 patients who underwent induction of labor, 208 (62.8%) delivered vaginally and 123 (37.1%) by cesarean delivery. Of the factors significantly associated with cesarean delivery, the final model included gestational age, simplified Bishop score, suspected intrauterine growth retardation, chronic hypertension, and body mass index. In the training cohort, the model correctly classified 72.3% of subjects with a sensitivity (cesarean delivery predicted/cesarean delivery performed) of 56.7% and a specificity (vaginal delivery predicted/vaginal delivery performed) of 84.1%. When applied to the validation cohort, 73.9% of subjects were correctly classified, with a sensitivity of 44.6% and specificity of 89.0%. Receiver-operating characteristic curves had an area under the curve of 0.75 for the training cohort and 0.77 for the validation cohort.

CONCLUSION

More than 60% of women undergoing induction of labor at <34 0/7 weeks deliver vaginally. For women undergoing induction of labor at <34 0/7 weeks, this prediction model rarely classifies individuals who can have a vaginal delivery as needing a cesarean delivery. This model may provide an accurate assessment tool to evaluate which patients will likely deliver vaginally to avoid the morbidity of cesarean delivery while conversely identifying subjects at high risk of cesarean delivery <34 0/7 weeks.

摘要

背景

当需要在34周前分娩时,许多医疗服务提供者会选择剖宫产而非引产,因为他们认为引产失败率很高。鉴于剖宫产的发病率,准确估计早产引产的成功率及与成功相关的因素对于管理决策至关重要。

目的

我们试图利用决定分娩时已知的因素,开发一种用于预测早产患者引产成功的模型。

研究设计

一项回顾性队列研究,对象为2011年至2015年期间所有孕周在23至34 0/7周之间接受引产的单胎活产儿。排除有严重胎儿畸形或未进行产时胎儿监测的妊娠。引产成功定义为经阴道分娩。该队列被随机分为一个训练队列以开发阴道分娩预测模型,以及一个验证队列以测试该模型。通过单因素分析确定与阴道分娩显著相关的因素,并将候选因素用于多因素逻辑回归模型。模型仅使用引产开始时已知的因素。绘制受试者工作特征曲线以估计模型的预测价值。评估模型的敏感性和特异性。

结果

在331例行引产的患者中,208例(62.8%)经阴道分娩,123例(37.1%)行剖宫产。在与剖宫产显著相关的因素中,最终模型纳入了孕周、简化Bishop评分、疑似胎儿生长受限、慢性高血压和体重指数。在训练队列中,该模型正确分类了72.3%的受试者,敏感性(预测剖宫产/实际剖宫产)为56.7%,特异性(预测阴道分娩/实际阴道分娩)为84.1%。应用于验证队列时,73.9%的受试者被正确分类,敏感性为44.6%,特异性为89.0%。训练队列的受试者工作特征曲线下面积为0.75,验证队列的为0.77。

结论

孕周<34 0/7周接受引产的女性中,超过60%经阴道分娩。对于孕周<34 0/7周接受引产的女性,该预测模型很少将能够经阴道分娩的个体误分类为需要剖宫产。该模型可能提供一种准确的评估工具,以评估哪些患者可能经阴道分娩,从而避免剖宫产的发病率,同时反过来识别孕周<34 0/7周时剖宫产高风险的受试者。

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