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分析技术对我们理解分娩自然史的影响:一项模拟研究。

Impact of analysis technique on our understanding of the natural history of labour: a simulation study.

机构信息

Sydney Institute for Women, Children and their Families, Sydney, NSW, Australia.

Faculty of Medicine and Health, The University of Sydney School of Public Health, Sydney, NSW, Australia.

出版信息

BJOG. 2021 Oct;128(11):1833-1842. doi: 10.1111/1471-0528.16719. Epub 2021 May 19.

Abstract

OBJECTIVE

To evaluate the discrepancy between historical and more recent descriptions of the first stage of labour by testing whether the statistical techniques used recently (repeated-measures polynomial and interval-censored regression) were appropriate for detection of periods of rapid acceleration of cervical dilatation as might occur at the time of transition from a latent to an active phase of labour.

DESIGN AND SETTING

A simulation study using regression techniques.

SAMPLE

We created a simulated data set for 500 000 labours with clearly defined latent and active phases using the parameters described by Friedman. Additionally, we created a data set comprising 500 000 labours with a progressively increasing rate of cervical dilatation.

METHODS

Repeated-measures polynomial regression was used to create summary labour curves based on simulated cervical examinations. Interval-censored regression was used to create centimetre-by-centimetre estimates of rates of cervical dilatation and their 95th centiles.

MAIN OUTCOME MEASURES

Labour summary curves and rates of cervical dilatation.

RESULTS

Repeated-measures polynomial regression did not detect the rapid acceleration in cervical dilatation (i.e. acceleration phase) and overestimated lengths of labour, especially at smaller cervical dilatations. There was a two-fold overestimation in the mean rate of cervical dilatation from 4 to 6 cm. Interval-censored regression overestimated median transit times, at 4- to 5-cm cervical dilatation or when cervical examinations occurred less frequently than 0.5- to 1.5-hourly.

CONCLUSION

Repeated-measures polynomial regression and interval-censored regression should not be routinely used to define labour progress because they do not accurately reflect the underlying data.

TWEETABLE ABSTRACT

Repeated-measures polynomial and interval-censored regression techniques are not appropriate to model first stage of labour.

摘要

目的

通过检验最近使用的统计技术(重复测量多项式和区间 censored 回归)是否适用于检测宫颈扩张快速加速期(可能发生在潜伏期向活跃期过渡时),来评估第一产程的历史描述和近期描述之间的差异。

设计和设置

使用回归技术的模拟研究。

样本

我们使用 Friedman 描述的参数为 50 万次分娩创建了一个具有明确潜伏期和活跃期的模拟数据集。此外,我们还创建了一个包含 50 万次分娩的数据集,这些分娩的宫颈扩张率逐渐增加。

方法

重复测量多项式回归用于根据模拟的宫颈检查创建分娩总结曲线。区间 censored 回归用于创建厘米级别的宫颈扩张率及其 95%百分位数的估计值。

主要观察指标

分娩总结曲线和宫颈扩张率。

结果

重复测量多项式回归未能检测到宫颈扩张的快速加速(即加速期),并高估了分娩的长度,尤其是在宫颈扩张较小的情况下。从 4 厘米到 6 厘米,宫颈扩张率的平均估计值高估了两倍。区间 censored 回归高估了 4 厘米至 5 厘米宫颈扩张或宫颈检查频率低于 0.5 小时至 1.5 小时时的中位数转移时间。

结论

重复测量多项式回归和区间 censored 回归不应该常规用于定义分娩进展,因为它们不能准确反映潜在数据。

推文摘要

重复测量多项式和区间 censored 回归技术不适用于建模第一产程。

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