• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

预测有一次剖宫产史孕妇引产成功的模型的开发与内部验证:一项队列研究(DEVI-CS模型)

Development and internal validation of a model predicting successful trial of labour among pregnant individuals with previous one caesarean section: A cohort study (DEVI-CS model).

作者信息

Pegu Bhabani, Subburaj Sathiya Priya, Chaturvedula Latha, Sarkar Sonali, Nair N Sreekumaran, Keepanasseril Anish

机构信息

Department of Obstetrics & Gynaecology, Jawaharlal Institute of Medical Education & Research, Puducherry 605006, India.

Preventive and Social Medicine, Jawaharlal Institute of Medical Education & Research, Puducherry 605006, India.

出版信息

Eur J Obstet Gynecol Reprod Biol. 2025 Feb;305:210-217. doi: 10.1016/j.ejogrb.2024.12.029. Epub 2024 Dec 16.

DOI:10.1016/j.ejogrb.2024.12.029
PMID:39708476
Abstract

OBJECTIVE

To develop and internally validate a model predicting successful trial of labour among pregnant women with previous caesarean scar.

DESIGN

Cohort study.

SETTING

Tertiary care and teaching hospital.

PARTICIPANTS

All pregnant women with one previous caesarean delivery, presenting with singleton pregnancies in cephalic presentation at a gestation age of 37 weeks or more between 2018 and 2022.

MAIN OUTCOME MEASURES

A stepwise multivariable logistic regression, followed by bootstrapping, was used to develop and validate the model. Success was defined as vaginal birth after caesarean section (VBAC) without complications for the mother and baby.

RESULT

Out of 4515 cases of TOLAC, 39.8 % had a successful trial of labour. Maternal age (OR = 0.950, 95 %CI: 0.927-0.974), previous baby weight (OR = 1.000, 95 %CI: 1.000-1.001), indication of previous caesarean section such as breech presentation (OR = 0.453, 95 %CI: 0.315-0.652), failed induction (OR = 0.346, 95 %CI: 0.267-0.447), BISHOP score (OR = 1.725, 95 %Cl: 1.673-1.774) and induction of labour (OR = 0.587, 95 %CI: 0.466-0.741) were the strongest predictors of successful TOLAC. DEVI-CS model showed good discrimination with an area under the curve (AUC) of 0.928(95 %CI: 0.921-0.936) and good agreement between predicted and observed probabilities. Decision curve analysis showed a net benefit between 5 % and 90 % between the predicted thresholds.

CONCLUSION

The new DEVI-CS prediction model, based on easily captured clinical variables, can quantify the chances of a successful trial of labour after a previous caesarean section. It could aid in shared decision-making regarding the mode of delivery among women with planning the trial of labour after caesarean section.

摘要

目的

开发并内部验证一个预测有剖宫产史孕妇引产成功的模型。

设计

队列研究。

地点

三级医疗和教学医院。

参与者

2018年至2022年间所有有一次剖宫产史、单胎妊娠、孕37周及以上且头先露的孕妇。

主要观察指标

采用逐步多变量逻辑回归,随后进行自抽样法,来开发和验证该模型。成功定义为剖宫产术后经阴道分娩(VBAC)且母婴均无并发症。

结果

在4515例引产病例中,39.8%引产成功。产妇年龄(OR = 0.950,95%CI:0.927 - 0.974)、前次婴儿体重(OR = 1.000,95%CI:1.000 - 1.001)、前次剖宫产指征如臀先露(OR = 0.453,95%CI:0.315 - 0.652)、引产失败(OR = 0.346,95%CI:0.267 - 0.447)、BISHOP评分(OR = 1.725,95%Cl:1.673 - 1.774)和引产(OR = 0.587,95%CI:0.466 - 0.741)是引产成功的最强预测因素。DEVI - CS模型显示出良好的辨别力,曲线下面积(AUC)为0.928(95%CI:0.921 - 0.936),预测概率与观察概率之间具有良好的一致性。决策曲线分析显示,在预测阈值之间,净效益在5%至90%之间。

结论

基于易于获取的临床变量的新DEVI - CS预测模型,可以量化既往剖宫产术后引产成功的几率。它有助于在有剖宫产史且计划引产的女性中,就分娩方式进行共同决策。

相似文献

1
Development and internal validation of a model predicting successful trial of labour among pregnant individuals with previous one caesarean section: A cohort study (DEVI-CS model).预测有一次剖宫产史孕妇引产成功的模型的开发与内部验证:一项队列研究(DEVI-CS模型)
Eur J Obstet Gynecol Reprod Biol. 2025 Feb;305:210-217. doi: 10.1016/j.ejogrb.2024.12.029. Epub 2024 Dec 16.
2
Factors associated with the outcome of TOLAC after one previous caesarean section: a retrospective cohort study.与剖宫产后再次经阴道分娩结局相关的因素:一项回顾性队列研究。
J Obstet Gynaecol. 2022 Apr;42(3):430-436. doi: 10.1080/01443615.2021.1916451. Epub 2021 Jun 21.
3
External validation of prediction models for vaginal delivery after the trial of labour among women with previous one caesarean section - A cohort study.既往剖宫产术后试产妇女阴道分娩预测模型的外部验证-队列研究。
Eur J Obstet Gynecol Reprod Biol. 2023 Dec;291:10-15. doi: 10.1016/j.ejogrb.2023.09.029. Epub 2023 Oct 2.
4
Predicting the success of vaginal birth after caesarean delivery: a retrospective cohort study in China.预测剖宫产术后阴道分娩的成功率:中国的一项回顾性队列研究。
BMJ Open. 2019 May 24;9(5):e027807. doi: 10.1136/bmjopen-2018-027807.
5
Predicting vaginal birth after caesarean section: Validation of the Grobman model in a New Zealand population.预测剖宫产术后阴道分娩:新西兰人群中 Grobman 模型的验证。
Aust N Z J Obstet Gynaecol. 2022 Oct;62(5):658-663. doi: 10.1111/ajo.13516. Epub 2022 Mar 27.
6
Validation of a prediction model for vaginal birth after caesarean.剖宫产术后阴道分娩预测模型的验证
J Obstet Gynaecol Can. 2013 Feb;35(2):119-124. doi: 10.1016/S1701-2163(15)31015-X.
7
Antenatal scoring system in predicting the success of planned vaginal birth following one previous caesarean section.预测既往有一次剖宫产史后计划阴道分娩成功率的产前评分系统。
J Obstet Gynaecol. 2018 Apr;38(3):339-343. doi: 10.1080/01443615.2017.1355896. Epub 2017 Oct 10.
8
External validation of a prediction model on vaginal birth after caesarean in a The Netherlands: a prospective cohort study.荷兰剖宫产术后阴道分娩预测模型的外部验证:一项前瞻性队列研究。
J Perinat Med. 2020 Nov 6;49(3):357-363. doi: 10.1515/jpm-2020-0308. Print 2021 Mar 26.
9
Factors Associated with Trial of Labour and Mode of Delivery in Robson Group 5: A Select Group of Women With Previous Caesarean Section.罗布森第5组中与引产及分娩方式相关的因素:一组有剖宫产史的特定女性群体
J Obstet Gynaecol Can. 2018 Jun;40(6):704-711. doi: 10.1016/j.jogc.2017.10.026. Epub 2018 Mar 2.
10
Are There Differences between Women who Choose Elective Repeat Caesarean Versus Trial of Labour in St. John's, NL?在加拿大纽芬兰与拉布拉多省圣约翰市,选择择期再次剖宫产与试产的女性之间存在差异吗?
J Obstet Gynaecol Can. 2018 Jul;40(7):903-909. doi: 10.1016/j.jogc.2017.10.021. Epub 2018 Apr 27.