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预测剖宫产的母婴特征:孕妇评分系统。

Maternal and fetal characteristics to predict c-section delivery: A scoring system for pregnant women.

机构信息

Maternal-Fetal Medicine Division, Department of Obstetrics and Gynaecology, Faculty of Medicine Universitas Indonesia and Cipto Mangunkusumo Hospital, Jakarta, Indonesia.

Faculty of Medicine Universitas Indonesia and Cipto Mangunkusumo Hospital, Jakarta, Indonesia.

出版信息

Womens Health (Lond). 2021 Jan-Dec;17:17455065211061969. doi: 10.1177/17455065211061969.

Abstract

INTRODUCTION

Cesarean section is one of the most common obstetrical interventions that has been performed at an increasing rate globally, due to both medical and non-medical reasons. This study aims to develop a prediction tool for pregnant women potentially needing c-section, such that necessary preparations from the mothers, families, and health providers can be made.

METHODS

A total of 603 pregnant women were recruited in the first phase of c-section prediction tool development. The association between the maternal and fetal factors on the risk of c-section were analyzed, followed by a stepwise multivariate regression analysis. In the next phase, 61 pregnant women were enrolled for external validation. Discrimination was assessed using area under the curve. The calibration plot was then made and assessed using the Hosmer-Lemeshow test.

RESULTS

There were 251 (41.6%) cases of vaginal delivery and 352 (58.4%) of c-section assessed. Multivariate analysis showed that gestational age < 37 wg (OR: 1.66, 95% CI: 1.10-2.51), pre-pregnancy body mass index (underweight) (OR: 0.40, 95% CI: 0.22-0.76), no history of vaginal delivery (OR: 2.66, 95% CI: 1.76-4.02), history of uterine surgery (OR: 8.34, 95% CI: 4.54-15.30), obstetrical complications (OR: 5.61, 95% CI: 3.53-8.90), birthweight ⩾ 3500 g (OR: 4.28, 95% CI: 2.16-8.47), and non-cephalic presentation (OR: 2.74, 95% CI: 1.53-4.89) were independently associated with c-section delivery. Those parameters were included in a 7-item scoring tool, with consecutive predictive scores of 1,-1,2,3,3,2,2,1. The area under the curve result was 0.813 (95% CI: 0.779-0.847), indicating a good predictive ability. The external validation showed AUC: 0.806, 95% CI: 0.694-0.917, Hosmer-Lemeshow test p = 0.666 and calibration plot coefficient of r = 0.939.

CONCLUSION

A total of 7 maternal-fetal factors were found to be strongly associated with c-section delivery, including gestational age < 37, maternal underweight body mass index, previous uterine surgery, obstetrical complications, birthweight ⩾ 3500, history of vaginal delivery, and non-cephalic presentation. Using these factors, a prediction tool was developed and validated with good quality.

摘要

简介

剖宫产术是全球范围内最常见的产科干预措施之一,由于医疗和非医疗原因,其实施率呈上升趋势。本研究旨在开发一种预测孕妇需要剖宫产的工具,以便母亲、家庭和医疗保健提供者做好必要的准备。

方法

在剖宫产预测工具的开发的第一阶段,共招募了 603 名孕妇。分析了产妇和胎儿因素与剖宫产风险的关系,然后进行逐步多变量回归分析。在下一阶段,有 61 名孕妇被纳入外部验证。采用曲线下面积评估鉴别能力。然后制作并使用 Hosmer-Lemeshow 检验评估校准图。

结果

评估了 251 例(41.6%)阴道分娩和 352 例(58.4%)剖宫产。多变量分析显示,妊娠龄<37 周(OR:1.66,95%CI:1.10-2.51)、孕前体重指数(消瘦)(OR:0.40,95%CI:0.22-0.76)、无阴道分娩史(OR:2.66,95%CI:1.76-4.02)、子宫手术史(OR:8.34,95%CI:4.54-15.30)、产科并发症(OR:5.61,95%CI:3.53-8.90)、出生体重≥3500g(OR:4.28,95%CI:2.16-8.47)和非头位(OR:2.74,95%CI:1.53-4.89)与剖宫产分娩独立相关。这些参数被纳入了一个 7 项评分工具中,连续预测评分分别为 1、-1、2、3、3、2、2、1。曲线下面积结果为 0.813(95%CI:0.779-0.847),表明具有良好的预测能力。外部验证显示 AUC:0.806,95%CI:0.694-0.917,Hosmer-Lemeshow 检验 p=0.666,校准图系数 r=0.939。

结论

共有 7 个母婴因素与剖宫产分娩密切相关,包括妊娠龄<37 周、产妇消瘦 BMI、既往子宫手术、产科并发症、出生体重≥3500g、阴道分娩史和非头位。使用这些因素开发并验证了一种具有良好质量的预测工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f33/8785277/dd368c715513/10.1177_17455065211061969-fig1.jpg

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