Cargando…

A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia

BACKGROUND: An attempt at vaginal delivery by a woman who has previously had a cesarean section is known as a trial of labor after cesarean section. The most important issues are how to accurately anticipate successful vaginal birth after cesarean surgery and how to calculate the likelihood of succe...

Descripción completa

Detalles Bibliográficos
Autores principales: Mesay, Filipos, Melese, Ergoye, Wudie, Gebiyaw, Feleke, Sefineh Fenta, Dessie, Anteneh Mengist
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880561/
https://www.ncbi.nlm.nih.gov/pubmed/36714193
http://dx.doi.org/10.2147/RMHP.S395388
_version_ 1784878941058629632
author Mesay, Filipos
Melese, Ergoye
Wudie, Gebiyaw
Feleke, Sefineh Fenta
Dessie, Anteneh Mengist
author_facet Mesay, Filipos
Melese, Ergoye
Wudie, Gebiyaw
Feleke, Sefineh Fenta
Dessie, Anteneh Mengist
author_sort Mesay, Filipos
collection PubMed
description BACKGROUND: An attempt at vaginal delivery by a woman who has previously had a cesarean section is known as a trial of labor after cesarean section. The most important issues are how to accurately anticipate successful vaginal birth after cesarean surgery and how to calculate the likelihood of success of vaginal birth after caesarean section that is suitable for women. Consequently, a tailored prediction of vaginal birth after caesarean section may result in a more effective counseling. OBJECTIVE: To create a clinical risk score and prediction model for the success of vaginal birth following a previous caesarean section in women. METHODS: A prognostic analysis was carried out at Felege Hiwot Comprehensive and Specialized Referral Hospital from 30 February 2017 to 30 March 2021. R statistical programming language version 4.0 was used for analysis once the data had been coded and entered into Epidata, version 3.02. Significant factors (P< 0.05) were kept in the backward multivariable logistic regression model, and variables with (P<0.25) from the bi-variable logistic regression analysis were also added. RESULTS: After a cesarean section, 67% of women were successful in giving birth vaginally. Previous successful vaginal birth after cesarean surgery, rupture of the membranes, and initiation time of ANC, the beginning of labor, parity and time since the previous delivery were remained in the final multivariable prediction model. The AUC of the model was 0.748 (95% CI: 0.714–0.781). CONCLUSION: Overall, this study demonstrated the likelihood of predicting vaginal birth utilizing the ideal confluence of parity, membrane rupture, and onset of labor, prior history of VBAC, inter-delivery gap, and ANC beginning time. Sixty-seven percent of VBACs were successful. As a result, this model may aid in identifying pregnant women who are candidates for VBAC and who have a better likelihood of success.
format Online
Article
Text
id pubmed-9880561
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-98805612023-01-28 A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia Mesay, Filipos Melese, Ergoye Wudie, Gebiyaw Feleke, Sefineh Fenta Dessie, Anteneh Mengist Risk Manag Healthc Policy Original Research BACKGROUND: An attempt at vaginal delivery by a woman who has previously had a cesarean section is known as a trial of labor after cesarean section. The most important issues are how to accurately anticipate successful vaginal birth after cesarean surgery and how to calculate the likelihood of success of vaginal birth after caesarean section that is suitable for women. Consequently, a tailored prediction of vaginal birth after caesarean section may result in a more effective counseling. OBJECTIVE: To create a clinical risk score and prediction model for the success of vaginal birth following a previous caesarean section in women. METHODS: A prognostic analysis was carried out at Felege Hiwot Comprehensive and Specialized Referral Hospital from 30 February 2017 to 30 March 2021. R statistical programming language version 4.0 was used for analysis once the data had been coded and entered into Epidata, version 3.02. Significant factors (P< 0.05) were kept in the backward multivariable logistic regression model, and variables with (P<0.25) from the bi-variable logistic regression analysis were also added. RESULTS: After a cesarean section, 67% of women were successful in giving birth vaginally. Previous successful vaginal birth after cesarean surgery, rupture of the membranes, and initiation time of ANC, the beginning of labor, parity and time since the previous delivery were remained in the final multivariable prediction model. The AUC of the model was 0.748 (95% CI: 0.714–0.781). CONCLUSION: Overall, this study demonstrated the likelihood of predicting vaginal birth utilizing the ideal confluence of parity, membrane rupture, and onset of labor, prior history of VBAC, inter-delivery gap, and ANC beginning time. Sixty-seven percent of VBACs were successful. As a result, this model may aid in identifying pregnant women who are candidates for VBAC and who have a better likelihood of success. Dove 2023-01-20 /pmc/articles/PMC9880561/ /pubmed/36714193 http://dx.doi.org/10.2147/RMHP.S395388 Text en © 2023 Mesay et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Mesay, Filipos
Melese, Ergoye
Wudie, Gebiyaw
Feleke, Sefineh Fenta
Dessie, Anteneh Mengist
A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title_full A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title_fullStr A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title_full_unstemmed A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title_short A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia
title_sort prognostic study for the development of risk prediction model for the success of vaginal birth following a cesarean surgery at felege hiwot comprehensive specialized hospital, northwest ethiopia
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9880561/
https://www.ncbi.nlm.nih.gov/pubmed/36714193
http://dx.doi.org/10.2147/RMHP.S395388
work_keys_str_mv AT mesayfilipos aprognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT meleseergoye aprognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT wudiegebiyaw aprognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT felekesefinehfenta aprognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT dessieantenehmengist aprognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT mesayfilipos prognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT meleseergoye prognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT wudiegebiyaw prognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT felekesefinehfenta prognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia
AT dessieantenehmengist prognosticstudyforthedevelopmentofriskpredictionmodelforthesuccessofvaginalbirthfollowingacesareansurgeryatfelegehiwotcomprehensivespecializedhospitalnorthwestethiopia