Evaluation of factors that predict the success rate of trial of labor after the cesarean section
Abstract Background For most women who have had a previous cesarean section, vaginal birth after cesarean section (VBAC) is a reasonable and safe choice, but which will increase the risk of adverse outcomes such as uterine rupture. In order to reduce the risk, we evaluated the factors that may affec...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-07-01
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| Series: | BMC Pregnancy and Childbirth |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12884-021-04004-z |
| _version_ | 1818619732776976384 |
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| author | Yang Mi Pengfei Qu Na Guo Ruimiao Bai Jiayi Gao Zhengfeei Ma Yiping He Caili Wang Xiaoqin Luo |
| author_facet | Yang Mi Pengfei Qu Na Guo Ruimiao Bai Jiayi Gao Zhengfeei Ma Yiping He Caili Wang Xiaoqin Luo |
| author_sort | Yang Mi |
| collection | DOAJ |
| description | Abstract Background For most women who have had a previous cesarean section, vaginal birth after cesarean section (VBAC) is a reasonable and safe choice, but which will increase the risk of adverse outcomes such as uterine rupture. In order to reduce the risk, we evaluated the factors that may affect VBAC and and established a model for predicting the success rate of trial of the labor after cesarean section (TOLAC). Methods All patients who gave birth at Northwest Women’s and Children’s Hospital from January 2016 to December 2018, had a history of cesarean section and voluntarily chose the TOLAC were recruited. Among them, 80% of the population was randomly assigned to the training set, while the remaining 20% were assigned to the external validation set. In the training set, univariate and multivariate logistic regression models were used to identify indicators related to successful TOLAC. A nomogram was constructed based on the results of multiple logistic regression analysis, and the selected variables included in the nomogram were used to predict the probability of successfully obtaining TOLAC. The area under the receiver operating characteristic curve was used to judge the predictive ability of the model. Results A total of 778 pregnant women were included in this study. Among them, 595 (76.48%) successfully underwent TOLAC, whereas 183 (23.52%) failed and switched to cesarean section. In multi-factor logistic regression, parity = 1, pre-pregnancy BMI < 24 kg/m2, cervical score ≥ 5, a history of previous vaginal delivery and neonatal birthweight < 3300 g were associated with the success of TOLAC. The area under the receiver operating characteristic curve in the prediction and validation models was 0.815 (95% CI: 0.762–0.854) and 0.730 (95% CI: 0.652–0.808), respectively, indicating that the nomogram prediction model had medium discriminative power. Conclusion The TOLAC was useful to reducing the cesarean section rate. Being primiparous, not overweight or obese, having a cervical score ≥ 5, a history of previous vaginal delivery or neonatal birthweight < 3300 g were protective indicators. In this study, the validated model had an approving predictive ability. |
| first_indexed | 2024-12-16T17:42:10Z |
| format | Article |
| id | doaj.art-a14aea3a1e4c4834858db9c70dd69b91 |
| institution | Directory Open Access Journal |
| issn | 1471-2393 |
| language | English |
| last_indexed | 2024-12-16T17:42:10Z |
| publishDate | 2021-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj.art-a14aea3a1e4c4834858db9c70dd69b912022-12-21T22:22:34ZengBMCBMC Pregnancy and Childbirth1471-23932021-07-012111910.1186/s12884-021-04004-zEvaluation of factors that predict the success rate of trial of labor after the cesarean sectionYang Mi0Pengfei Qu1Na Guo2Ruimiao Bai3Jiayi Gao4Zhengfeei Ma5Yiping He6Caili Wang7Xiaoqin Luo8Department of Obstetrics and Gynecology, Northwest Women’s and Children’s HospitalTranslational Medicine Center, Northwest Women’s and Children’s HospitalDepartment of Obstetrics and Gynecology, Northwest Women’s and Children’s HospitalDepartment of Obstetrics and Gynecology, Northwest Women’s and Children’s HospitalDepartment of Nutrition and Food Safety, School of Public Health, Xi’an Jiaotong UniversityDepartment of Health and Environmental Sciences, Xi’an Jiaotong-Liverpool UniversityDepartment of Obstetrics and Gynecology, Northwest Women’s and Children’s HospitalDepartment of Obstetrics and Gynecology, Northwest Women’s and Children’s HospitalDepartment of Nutrition and Food Safety, School of Public Health, Xi’an Jiaotong UniversityAbstract Background For most women who have had a previous cesarean section, vaginal birth after cesarean section (VBAC) is a reasonable and safe choice, but which will increase the risk of adverse outcomes such as uterine rupture. In order to reduce the risk, we evaluated the factors that may affect VBAC and and established a model for predicting the success rate of trial of the labor after cesarean section (TOLAC). Methods All patients who gave birth at Northwest Women’s and Children’s Hospital from January 2016 to December 2018, had a history of cesarean section and voluntarily chose the TOLAC were recruited. Among them, 80% of the population was randomly assigned to the training set, while the remaining 20% were assigned to the external validation set. In the training set, univariate and multivariate logistic regression models were used to identify indicators related to successful TOLAC. A nomogram was constructed based on the results of multiple logistic regression analysis, and the selected variables included in the nomogram were used to predict the probability of successfully obtaining TOLAC. The area under the receiver operating characteristic curve was used to judge the predictive ability of the model. Results A total of 778 pregnant women were included in this study. Among them, 595 (76.48%) successfully underwent TOLAC, whereas 183 (23.52%) failed and switched to cesarean section. In multi-factor logistic regression, parity = 1, pre-pregnancy BMI < 24 kg/m2, cervical score ≥ 5, a history of previous vaginal delivery and neonatal birthweight < 3300 g were associated with the success of TOLAC. The area under the receiver operating characteristic curve in the prediction and validation models was 0.815 (95% CI: 0.762–0.854) and 0.730 (95% CI: 0.652–0.808), respectively, indicating that the nomogram prediction model had medium discriminative power. Conclusion The TOLAC was useful to reducing the cesarean section rate. Being primiparous, not overweight or obese, having a cervical score ≥ 5, a history of previous vaginal delivery or neonatal birthweight < 3300 g were protective indicators. In this study, the validated model had an approving predictive ability.https://doi.org/10.1186/s12884-021-04004-zVaginal birth after cesarean sectionTrial of the labor after cesarean sectionIntrapartum managementPrediction model |
| spellingShingle | Yang Mi Pengfei Qu Na Guo Ruimiao Bai Jiayi Gao Zhengfeei Ma Yiping He Caili Wang Xiaoqin Luo Evaluation of factors that predict the success rate of trial of labor after the cesarean section BMC Pregnancy and Childbirth Vaginal birth after cesarean section Trial of the labor after cesarean section Intrapartum management Prediction model |
| title | Evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| title_full | Evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| title_fullStr | Evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| title_full_unstemmed | Evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| title_short | Evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| title_sort | evaluation of factors that predict the success rate of trial of labor after the cesarean section |
| topic | Vaginal birth after cesarean section Trial of the labor after cesarean section Intrapartum management Prediction model |
| url | https://doi.org/10.1186/s12884-021-04004-z |
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