Literature DB >> 25801723

Predicting the chance of vaginal delivery after one cesarean section: validation and elaboration of a published prediction model.

Marie C Fagerberg1, Karel Maršál2, Karin Källén3.   

Abstract

OBJECTIVE: We aimed to validate a widely used US prediction model for vaginal birth after cesarean (Grobman et al. [8]) and modify it to suit Swedish conditions. STUDY
DESIGN: Women having experienced one cesarean section and at least one subsequent delivery (n=49,472) in the Swedish Medical Birth Registry 1992-2011 were randomly divided into two data sets. In the development data set, variables associated with successful trial of labor were identified using multiple logistic regression. The predictive ability of the estimates previously published by Grobman et al., and of our modified and new estimates, respectively, was then evaluated using the validation data set. The accuracy of the models for prediction of vaginal birth after cesarean was measured by area under the receiver operating characteristics curve.
RESULTS: For maternal age, body mass index, prior vaginal delivery, and prior labor arrest, the odds ratio estimates for vaginal birth after cesarean were similar to those previously published. The prediction accuracy increased when information on indication for the previous cesarean section was added (from area under the receiver operating characteristics curve=0.69-0.71), and increased further when maternal height and delivery unit cesarean section rates were included (area under the receiver operating characteristics curve=0.74). The correlation between the individual predicted vaginal birth after cesarean probability and the observed trial of labor success rate was high in all the respective predicted probability decentiles.
CONCLUSION: Customization of prediction models for vaginal birth after cesarean is of considerable value. Choosing relevant indicators for a Swedish setting made it possible to achieve excellent prediction accuracy for success in trial of labor after cesarean. During the delicate process of counseling about preferred delivery mode after one cesarean section, considering the results of our study may facilitate the choice between a trial of labor or an elective repeat cesarean section.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Elective repeat cesarean; Prediction model; Vaginal birth after cesarean

Mesh:

Year:  2015        PMID: 25801723     DOI: 10.1016/j.ejogrb.2015.02.031

Source DB:  PubMed          Journal:  Eur J Obstet Gynecol Reprod Biol        ISSN: 0301-2115            Impact factor:   2.435


  8 in total

1.  Racial and Ethnic Disparities Among Women Undergoing a Trial of Labor After Cesarean Delivery: Performance of the VBAC Calculator with and without Patients' Race/Ethnicity.

Authors:  Ayisha Buckley; Stephanie Sestito; Tonia Ogundipe; Jacqueline Roig; Henri Mitchell Rosenberg; Natalie Cohen; Kelly Wang; Guillaume Stoffels; Teresa Janevic; Chelsea DeBolt; Camila Cabrera; Elizabeth Cochrane; Jill Berkin; Angela Bianco; Luciana Vieira
Journal:  Reprod Sci       Date:  2022-05-09       Impact factor: 2.924

2.  Birth by Caesarean Section and the Risk of Adult Psychosis: A Population-Based Cohort Study.

Authors:  Sinéad M O'Neill; Eileen A Curran; Christina Dalman; Louise C Kenny; Patricia M Kearney; Gerard Clarke; John F Cryan; Timothy G Dinan; Ali S Khashan
Journal:  Schizophr Bull       Date:  2015-11-27       Impact factor: 9.306

3.  Validation of a Prediction Model for Vaginal Birth after Cesarean Delivery Reveals Unexpected Success in a Diverse American Population.

Authors:  Melanie Mai Maykin; Amanda J Mularz; Lydia K Lee; Stephanie Gaw Valderramos
Journal:  AJP Rep       Date:  2017-01

4.  Prediction of vaginal birth after cesarean delivery in Chinese parturients.

Authors:  Juan Wen; Xuejing Song; Hongjuan Ding; Xiaofeng Shen; Rong Shen; Ling-Qun Hu; Wei Long
Journal:  Sci Rep       Date:  2018-02-15       Impact factor: 4.379

5.  Validation of a predictive model for successful vaginal birth after cesarean section.

Authors:  Javier Enrique Fonseca; Juliana Lucía Rodriguez; Durley Maya Salazar
Journal:  Colomb Med (Cali)       Date:  2019-03-30

Review 6.  Application of predictive model for vaginal birth after caesarean delivery.

Authors:  Ruchi Pan; Libin An; Wanwan Zhang; Wentao Li
Journal:  Int J Nurs Sci       Date:  2017-12-26

7.  Low risk pregnancies after a cesarean section: Determinants of trial of labor and its failure.

Authors:  Sjur Lehmann; Elham Baghestan; Per E Børdahl; Lorentz M Irgens; Svein Rasmussen
Journal:  PLoS One       Date:  2020-01-13       Impact factor: 3.240

8.  Predicting vaginal birth after previous cesarean: Using machine-learning models and a population-based cohort in Sweden.

Authors:  Charlotte Lindblad Wollmann; Kyle D Hart; Can Liu; Aaron B Caughey; Olof Stephansson; Jonathan M Snowden
Journal:  Acta Obstet Gynecol Scand       Date:  2020-10-31       Impact factor: 3.636

  8 in total

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