EASI: Shear Wave Elastography Assessment For Predicting Success Of Labor Induction

项目摘要 最新数据显示，美国每4名孕妇中就有1人接受了引产， 使其成为当今最常见的产科干预措施之一。然而，从尊重的角度来看，它是最不可预测的 对结局(阴道分娩与剖腹产)，以及最佳实践方面研究最少的之一。这个 近年来，人工晶状体的频率有所增加，同时剖腹产的数量也在增加。这个 人工晶状体和剖宫产之间的关系并不简单，但很明显，这两种干预措施都有 成为重要的公共卫生问题，因为它们相关的资源利用率和发病率的增加。fi。 具体地说，在接受引产和剖腹产相关的妇女中，利用率更高 母亲和新生儿的发病率(近期和未来)都较高。 宫颈准备是人工晶状体成功的关键。这是合乎逻辑的，因为宫颈必须打开才能让婴儿分娩。 鉴于此，今天的医生依靠对宫颈的主观临床评估几乎是令人难以置信的 对于关于谁应该接受人工晶状体手术的重要决定，或者如果医学上表明分娩，谁应该接受人工晶状体手术的重要决定 人工晶状体前宫颈需要成熟(软化)，哪种类型的成熟最好。为了评估颈椎的亲和度， 医生对宫颈的特征进行评分，如宫颈扩张、柔软和长度。 阴道检查。这些分数被组合成一个总结性毕晓普分数(BS)，该分数被认为是预测成功的指标 人工晶状体。从业者经常抱怨BS的主观性和缺乏重复性，但许多人并非如此 甚至知道另一个重要的问题：BS是在50多年前开发的，目的是 今天已经不再重要了。特别是，它是为了预测有fi病史的妇女的分娩时间而开发的。 本期妊娠足月经阴道分娩。这一信息最终被利用来暗示 这些女性的人工晶状体植入术取得了成功。今天我们知道，这样的女人成功的机会是如此之高，以至于她 宫颈检查几乎无关紧要。但在产科实践中，BS仍然每天用于预测 在任何孕龄从未生过孩子的妇女经阴道分娩的机会。不出所料， 这种重新定位的人工晶状体并不能很好地预测人工晶状体的成功。 也就是说，宫颈扩张和柔软度等特征可以预测 宫颈会打开，因为这些是潜在生物力学特征的物理表现， 决定组织的功能。定量超声(Qus)技术可以提供客观的、可测量的信息。 关于组织属性，如柔软度，这意味着它们可以对预测的个性化指标做出贡献 接近人工晶状体，并对其抱有期望。为此，本提案描述了一种前瞻性的、观察性的、 一项旨在评估QUS技术是否能提高人工晶状体成功率预测的横断面研究。

Project Summary The most recent data indicate that 1 in 4 pregnant women in the U.S. undergoes induction of labor (IOL), making this one of today's most common obstetrical interventions. Yet it is one of the least predictable with respect to outcome (vaginal vs. cesarean delivery) and one of the least well studied with respect to best practice. The frequency of IOL has increased in recent years, paralleled by an increase in the number of cesarean deliveries. The relationship between IOL and cesarean delivery is not straightforward, but it is clear that both interventions have become significant public health issues because of their associated increased resource utilization and morbidity. Specifically, higher utilization is seen in women who undergo labor induction and cesarean delivery is associated with higher morbidity (immediate and future) for both mother and neonate. Cervical readiness is crucial to IOL success. This is logical since the cervix must open for the baby to deliver. Given this, it is almost unbelievable that today's practitioner relies on a subjective clinical assessment of cervical "favorability" for important decisions about who should undergo IOL or, if delivery is medically indicated, whose cervix needs ripening (softening) before IOL and what type of ripening would be best. To assess cervical favorability, the practitioner assigns points to cervical characteristics such as dilatation, softness, and length as assessed per vaginal exam. The points are combined into a summative Bishop score (BS), which is supposed to predict success of IOL. Practitioners often complain about the subjectivity and lack of reproducibility of the BS, but many do not even know about another significant issue: the BS was developed more than 50 years ago for a purpose that today is no longer relevant. Specifically, it was developed to predict time to delivery in a woman with a history of vaginal delivery at full term gestation in the current pregnancy. This information was eventually leveraged to imply success from IOL in these women. Today we know that the chance of success in such a woman is so high that her cervical exam is almost irrelevant. But the BS is still used on a daily basis in obstetrical practice to predict the chance of vaginal delivery in a woman at any gestational age who has never before had a baby. Unsurprisingly, this re-purposed BS is a poor predictor of IOL success. That said, it certainly makes sense that characteristics such as cervical dilatation and softness would predict how well the cervix will open because these are physical manifestations of underlying biomechanical characteristics that dictate tissue function. Quantitative ultrasound (QUS) techniques can provide objective, measurable information about tissue properties such as softness, which means that they could contribute to a personalized metric to predict approach to, and expectations for, IOL. Toward that end, this proposal describes a prospective, observational, cross-sectional study designed to evaluate whether QUS techniques can improve prediction of IOL success.