Third-trimester prediction of successful vaginal birth after one cesarean delivery—A Swedish model
(2020) In Acta Obstetricia et Gynecologica Scandinavica 99(5). p.660-668- Abstract
Introduction: The objective was to create a clinically useful prediction model for vaginal birth in trial of labor after one cesarean section, appropriate for a third trimester consultation. Material and methods: Women with one cesarean section and at least one following delivery (N = 38 686) in the Swedish Medical Birth Register, 1998-2013, were studied. The women were randomly divided into one development and one validation data set. From the development data set, variables associated with vaginal birth after cesarean (VBAC) were identified by univariable logistic regression. Stepwise backward selection was performed until all variables were statistically significant. From the final fitted multivariable logistic model, likelihood... (More)
Introduction: The objective was to create a clinically useful prediction model for vaginal birth in trial of labor after one cesarean section, appropriate for a third trimester consultation. Material and methods: Women with one cesarean section and at least one following delivery (N = 38 686) in the Swedish Medical Birth Register, 1998-2013, were studied. The women were randomly divided into one development and one validation data set. From the development data set, variables associated with vaginal birth after cesarean (VBAC) were identified by univariable logistic regression. Stepwise backward selection was performed until all variables were statistically significant. From the final fitted multivariable logistic model, likelihood ratios were calculated, in order to transpose odds ratios into clinically useful measurements. A constant, based on the delivery ward VBAC in trial of labor rate, was used. By applying the likelihood ratios on the validation data set, the VBAC chance for each woman was estimated with the Bayesian theorem, and the ability of the model to predict VBAC was explored using receiver operating characteristics (ROC) curves. Results: A previous VBAC, and a previous cesarean section for non-cephalic presentation, were the strongest VBAC predictors. The lowest chances were found for a previous cesarean section due to dystocia, and among women with <18 months since the last cesarean section. The area under the ROC curve was 0.67. Conclusions: The new model was satisfactory in predicting VBAC in trial of labor. Developed as a software application, it would become a clinically useful decision-aid.
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- author
- Carlsson Fagerberg, Marie LU and Källén, Karin LU
- organization
- publishing date
- 2020-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- cesarean section, decision aid, elective repeat cesarean section, prediction model, trial of labor, vaginal birth after cesarean
- in
- Acta Obstetricia et Gynecologica Scandinavica
- volume
- 99
- issue
- 5
- pages
- 9 pages
- publisher
- Wiley-Blackwell
- external identifiers
-
- scopus:85076921455
- pmid:31788783
- ISSN
- 0001-6349
- DOI
- 10.1111/aogs.13783
- language
- English
- LU publication?
- yes
- id
- 2263fd0a-fc8e-48f3-9105-699077bf7381
- date added to LUP
- 2020-01-10 10:54:46
- date last changed
- 2024-06-26 08:37:18
@article{2263fd0a-fc8e-48f3-9105-699077bf7381,
abstract = {{<p>Introduction: The objective was to create a clinically useful prediction model for vaginal birth in trial of labor after one cesarean section, appropriate for a third trimester consultation. Material and methods: Women with one cesarean section and at least one following delivery (N = 38 686) in the Swedish Medical Birth Register, 1998-2013, were studied. The women were randomly divided into one development and one validation data set. From the development data set, variables associated with vaginal birth after cesarean (VBAC) were identified by univariable logistic regression. Stepwise backward selection was performed until all variables were statistically significant. From the final fitted multivariable logistic model, likelihood ratios were calculated, in order to transpose odds ratios into clinically useful measurements. A constant, based on the delivery ward VBAC in trial of labor rate, was used. By applying the likelihood ratios on the validation data set, the VBAC chance for each woman was estimated with the Bayesian theorem, and the ability of the model to predict VBAC was explored using receiver operating characteristics (ROC) curves. Results: A previous VBAC, and a previous cesarean section for non-cephalic presentation, were the strongest VBAC predictors. The lowest chances were found for a previous cesarean section due to dystocia, and among women with <18 months since the last cesarean section. The area under the ROC curve was 0.67. Conclusions: The new model was satisfactory in predicting VBAC in trial of labor. Developed as a software application, it would become a clinically useful decision-aid.</p>}},
author = {{Carlsson Fagerberg, Marie and Källén, Karin}},
issn = {{0001-6349}},
keywords = {{cesarean section; decision aid; elective repeat cesarean section; prediction model; trial of labor; vaginal birth after cesarean}},
language = {{eng}},
number = {{5}},
pages = {{660--668}},
publisher = {{Wiley-Blackwell}},
series = {{Acta Obstetricia et Gynecologica Scandinavica}},
title = {{Third-trimester prediction of successful vaginal birth after one cesarean delivery—A Swedish model}},
url = {{http://dx.doi.org/10.1111/aogs.13783}},
doi = {{10.1111/aogs.13783}},
volume = {{99}},
year = {{2020}},
}