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Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey

INTRODUCTION: With the wide adoption of the two-child policy in China since 2016, a large percentage of women with a history of caesarean delivery plan to have a second child. Accordingly, the rate of vaginal birth after caesarean (VBAC) delivery is increasing. Women attempting repeat VBAC may exper...

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Autores principales: Zhu, Weiying, Ai, Ling, Feng, Ying, Yuan, Haiyan, Wang, Yu, Wang, Meitang, Mei, Zubing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103394/
https://www.ncbi.nlm.nih.gov/pubmed/33952555
http://dx.doi.org/10.1136/bmjopen-2020-047433
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author Zhu, Weiying
Ai, Ling
Feng, Ying
Yuan, Haiyan
Wang, Yu
Wang, Meitang
Mei, Zubing
author_facet Zhu, Weiying
Ai, Ling
Feng, Ying
Yuan, Haiyan
Wang, Yu
Wang, Meitang
Mei, Zubing
author_sort Zhu, Weiying
collection PubMed
description INTRODUCTION: With the wide adoption of the two-child policy in China since 2016, a large percentage of women with a history of caesarean delivery plan to have a second child. Accordingly, the rate of vaginal birth after caesarean (VBAC) delivery is increasing. Women attempting repeat VBAC may experience multiple morbidities, which is also one of the leading causes of maternal and perinatal mortality. However, it remains to be addressed how we evaluate factors for successful VBAC. This study aims to use a novel approach to identify a set of potential predictive factors for successful VBAC, especially for Chinese women, to be included in prediction models which can be most applicable to pregnant women in China. We plan to assess all potential predictive factors collected through a comprehensive literature review. Then the certainty of the evidence for the identified potential predictive factors will be assessed using the Grading of Recommendations Assessment, Development and Evaluation process. Finally, a two-round international Delphi survey will be conducted to determine the level of consensus. METHODS AND ANALYSIS: This study will apply a methodology through an evidence-based approach. A long list of potential predictive factors for successful VBAC will be extracted and identified through the following stages: First, an up-to-date systematic review of the published literature will be conducted to extract identified potential predictive factors for successful VBAC. Second, an online Delphi survey will be performed to achieve expert consensus on which factors should be included in future prediction models. The online questionnaires will be developed in the field of patient, maternal and fetal-related factors. A two-round international Delphi survey will be distributed to the expert panel in the field of perinatal medicine using Google Forms. Experts will be asked to score each factor using the 9-point Likert rating scale to establish potential predictive factors for the successful VBAC. The expert panel will determine on whether to include, potentially include or exclude predictive factors, based on a systematic review of clinical evidence and the Delphi method. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board of the Jiaxing Maternity and Children Healthcare Hospital (approval number: 2019–79). The results of this study will be submitted to international peer-reviewed journals or conferences in perinatal medicine or obstetrics.
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spelling pubmed-81033942021-05-24 Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey Zhu, Weiying Ai, Ling Feng, Ying Yuan, Haiyan Wang, Yu Wang, Meitang Mei, Zubing BMJ Open Obstetrics and Gynaecology INTRODUCTION: With the wide adoption of the two-child policy in China since 2016, a large percentage of women with a history of caesarean delivery plan to have a second child. Accordingly, the rate of vaginal birth after caesarean (VBAC) delivery is increasing. Women attempting repeat VBAC may experience multiple morbidities, which is also one of the leading causes of maternal and perinatal mortality. However, it remains to be addressed how we evaluate factors for successful VBAC. This study aims to use a novel approach to identify a set of potential predictive factors for successful VBAC, especially for Chinese women, to be included in prediction models which can be most applicable to pregnant women in China. We plan to assess all potential predictive factors collected through a comprehensive literature review. Then the certainty of the evidence for the identified potential predictive factors will be assessed using the Grading of Recommendations Assessment, Development and Evaluation process. Finally, a two-round international Delphi survey will be conducted to determine the level of consensus. METHODS AND ANALYSIS: This study will apply a methodology through an evidence-based approach. A long list of potential predictive factors for successful VBAC will be extracted and identified through the following stages: First, an up-to-date systematic review of the published literature will be conducted to extract identified potential predictive factors for successful VBAC. Second, an online Delphi survey will be performed to achieve expert consensus on which factors should be included in future prediction models. The online questionnaires will be developed in the field of patient, maternal and fetal-related factors. A two-round international Delphi survey will be distributed to the expert panel in the field of perinatal medicine using Google Forms. Experts will be asked to score each factor using the 9-point Likert rating scale to establish potential predictive factors for the successful VBAC. The expert panel will determine on whether to include, potentially include or exclude predictive factors, based on a systematic review of clinical evidence and the Delphi method. ETHICS AND DISSEMINATION: The study was approved by the Institutional Review Board of the Jiaxing Maternity and Children Healthcare Hospital (approval number: 2019–79). The results of this study will be submitted to international peer-reviewed journals or conferences in perinatal medicine or obstetrics. BMJ Publishing Group 2021-05-05 /pmc/articles/PMC8103394/ /pubmed/33952555 http://dx.doi.org/10.1136/bmjopen-2020-047433 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Obstetrics and Gynaecology
Zhu, Weiying
Ai, Ling
Feng, Ying
Yuan, Haiyan
Wang, Yu
Wang, Meitang
Mei, Zubing
Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title_full Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title_fullStr Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title_full_unstemmed Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title_short Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey
title_sort factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a delphi survey
topic Obstetrics and Gynaecology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8103394/
https://www.ncbi.nlm.nih.gov/pubmed/33952555
http://dx.doi.org/10.1136/bmjopen-2020-047433
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