Verification a model of predicting vaginal birth after cesarean delivery in Chinese pregnant women

External validation of prediction models for vaginal delivery after the trial of labour among women with previous one caesarean section - A cohort study

OBJECTIVE

To externally validate three predictive models (the Grobman model (2007), the Zhang model (2020), and the Grobman model (2021)) for identifying women with increased chances of a successful trial of labour after caesarean section (TOLAC).

METHODS

This retrospective observational cohort study was conducted in a tertiary teaching hospital from 2018 to 2021. Individual probabilities were calculated for women with previous one caesarean section who underwent TOLAC at term, using the predicted probabilities from the logistic regression models. The primary outcome of this study was vaginal delivery following attempted TOLAC. The predictive ability of the models was assessed using the area under the receiver operative characteristics curves (AUC) and a calibration graph.

RESULTS

Of 1515 eligible women who underwent TOLAC, we found an overall rate of successful TOLAC of 60.3 %. No significant difference was noticed in adverse scar outcome and neonatal morbidity while comparing successful and failed TOLAC. The discriminative ability of Grobman-2007 and Grobman-2021 and the Zhang model were fair to poor with the AUC of 0.54(95 % CI 0.51-0.57), 0.62(95 % CI 0.59-0.65) and 0.66(95 % CI 0.63-0.69) respectively. The agreement between the observed rates of TOLAC success and the predicted probabilities for all three models was poor.

CONCLUSION

The performance of all three models predicting success after TOLAC was poor in the study population. A population-specific model may be needed, with the addition of factors influencing the labour, such as the methods of induction, which may aid in predicting the outcome.

Mid-trimester cervical length and prediction of vaginal birth after cesarean delivery in Chinese parturients: A retrospective study

BACKGROUND

A successful trial of labor after cesarean (TOLAC) is linked with the best maternal/neonatal outcomes and is more cost-effective than elective repeat cesarean section (ERCS). Predictive models of vaginal birth after cesarean (VBAC) have been established worldwide to improve the success rate of TOLAC.

OBJECTIVE

To validate a VBAC prediction model (the updated Grobman's predictive model without ethnicity) and identify whether mid-trimester cervical lengths (MCL) improve the prediction of VBAC among Chinese women undergoing a TOLAC.

METHODS

In this retrospective cohort study, the inclusion criteria were a previous history of cesarean delivery (CD) as well as a singleton gestation in the vertex position with routine CL measurements between 20 and 24 weeks and the experience of a TOLAC. MCL as well as identifiable characteristics in early prenatal care that have been used in updated Grobman's predictive model (maternal age, height, pre-pregnancy weight, vaginal delivery history, VBAC history, arrest disorder in previous CD, and treated chronic hypertension) were obtained from the medical records. Associations of maternal characteristics and MCL with VBAC were evaluated using multivariate logistic regression. Two multivariable regression models with and without MCL as one of the risk factors were established and their predictive accuracy for VBAC was critically compared based on receiver-operating characteristic (ROC) curves.

RESULTS

This study involved 409 women, among which, 347 (84.8%) achieved a VBAC. The mean MCL was significantly shorter in women who had a successful VBAC than in those who required an intrapartum CD (4.16±0.49 cm vs. 4.35±0.46 cm, P=0.007). Multivariable logistic regression revealed that a longer MCL (cm) was significantly related to a lower success rate of TOLAC [adjusted odds ratio (aOR), 0.48; 95% confidence interval (CI), 0.26-0.88]. The areas under the ROCs of Grobman's model with and without MCL as one of the risk factors were 0.785 (95% CI, 0.725-0.844) and 0.774 (95% CI, 0.710-0.837), respectively, but not significantly different (Z = -0.968, P = 0.333).

CONCLUSIONS

We first evaluated the efficiency of the updated Grobman's model (without race and ethnicity) in the Chinese population. The area under the curve is relatively high, indicating that the model can be used efficiently in China. The shorter MCL was associated with a greater chance of VBAC and MCL was the independent factor from the factors of Grobman's model. However, the predictive capacity of the modified model by adding MCL as one of the risk factors did not improve significantly.

Factors associated with successful vaginal birth after one lower uterine transverse cesarean section delivery

A Trial of labor after cesarean section is an attempt to deliver vaginally by a woman who had a previous cesarean delivery and when achieved by a vaginal delivery it is called successful vaginal birth after cesarean section. Vaginal birth after a caesarian section is a preferred method to decrease complications associated with repeated caesarian section delivery for both mother and fetus. It has a higher success rate when the right women are selected for a trial of labor. This study aimed to assess factors associated with successful vaginal birth after one lower uterine transverse cesarean section and to validate the Flamm and Geiger score at the public hospitals of Bahir Dar City, Northwest, Ethiopia, 2021. A health facility-based retrospective cross-sectional study was conducted from March 1 to 15/2021. A medical record review of 408 women charts with a trial of labor after one lower uterine transverse cesarean section from January 1/2020 to December 31/2020 was done and 345 women charts with complete maternal and fetal information were included in the study with a response rate of 84.6%. The data were collected using a structured checklist, entered into Epi data 3.1, and analyzed using SPSS 25.0 version. Logistic regression analyses were done to estimate the crude and adjusted odds ratio with a confidence interval of 95% and a P-value of less than 0.05 considered statistically significant. This study identified that the trial of labor after cesarean section rate was 69.5%, and the success rate of vaginal birth after one lower uterine transverse cesarean section was 35.07%. Of the failed trial of labor, fetal distress (38.9%) and failed progress of labor (32.1%) were the main indications for an emergency cesarean section. The maternal age group of 21-30 years, prior vaginal birth after or before cesarean section, non-recurring indication (fetal distress and malpresentation), ruptured membrane, cervical dilatation ≥ 4 cm, cervical effacement ≥ 50%, and low station (≥ 0) at admission were associated with successful vaginal birth after one lower uterine transverse cesarean section. For the Flamm and Geiger score at a cut point of 5, the sensitivity and specificity were 73.6% and 86.6% respectively. In this study area, the trial of labor after cesarean section rate is encouraging, however, the success rate of vaginal birth after one lower uterine transverse caesarian section was lower. The maternal socio-demographic and obstetric-related factors were significantly associated with successful vaginal birth after one lower transverse caesarian section delivery. This study indicated that when the Flamm and Geiger score increases, the chance of successful vaginal birth after one lower uterine transverse caesarian section also increases. We suggest emphasizing counselling and encouraging the women, as their chance of successful vaginal delivery will be high in the subsequent pregnancy, especially if the indications of primary caesarian section delivery were non-recurring.

Prediction models of vaginal birth after cesarean delivery: A systematic review

BACKGROUND

Cesarean section rates are rising in the world. Women with a history of cesarean section will select a cesarean section at the next pregnancy. An objective and accurate prediction about the success rate of vaginal delivery after cesarean section can help women to reduce the complications caused by cesarean section, shorten the time spent in the hospital, and effectively plan medical resources.

OBJECTIVE

To systematically review and critically assess the existing prediction models of vaginal delivery after cesarean section.

METHODS

Some databases (PubMed, Web of Science, EMBASE, the Cochrane Library, Cumulative Index to Nursing and Allied Health Literature) were searched from 2000 to 2021 for studies regarding the prediction model of vaginal birth after cesarean delivery. The researchers successively conducted independent literature screening, data extraction and quality evaluation of the included literature, and then utilized the Prediction model Risk of Bias Assessment Tool to assess the methodological quality of the models in the included studies.

RESULTS

A total of 33 studies were included, in which 20 prediction models were identified. Sixteen studies involved external validation of existing models (Grobman's models). In the 20 prediction models, 12 were internally validated, only three had external validation, and seven models were not explicitly reported, with the area under the curve ranging from 0.660 to 0.953; The most common predictors included in the model were body mass index and previous vaginal delivery, followed by maternal age, previous cesarean delivery indication, history of vaginal birth after cesarean, fetal weight, and Bishop's score, gestational age, history of vaginal birth after cesarean, maternal race; The prediction effect of Grobman's model was validated in multiple external populations; The majority of the studies(n = 27) had high risk of bias in the of the Prediction model Risk of Bias Assessment Tool.

CONCLUSIONS

This review provides obstetricians and midwives with important information about the prediction models of vaginal birth after cesarean section, which has been reported optimistic predictive performance and acceptable predictive power. However, the majority of the development studies have methodological limitations, which may hinder the widely application of these models by obstetricians. Further studies are supposed to develop predictive models with low risk of bias, and conduct internal and external validation, providing pragmatic and practical predictions to obstetricians.

PROSPERO REGISTRATION NUMBER

CRD42022299048.

Determinants of successful trial of labor after a previous cesarean delivery in East Wollega, Western Ethiopia: A case–control study

Objective:

Vaginal birth after cesarean could be considered a reasonable and safe option for most women with a previous cesarean section. However, it is not easy to select pregnant mothers who are a candidate for a trial of labor after cesarean. Therefore, this study is aimed to identify determinants of successful vaginal birth after previous cesarean delivery in public hospitals in East Wollega, Western Ethiopia, 2020.

Methods:

A facility-based unmatched case–control study was conducted on 115 cases and 115 controls. Cases were those women who successfully delivered vaginally and controls were those women delivered by cesarean section after trial of labor. Data were collected using a pre-tested structured questionnaire and organized using Epidata version 3.1. Descriptive analysis and logistic regressions were performed. The adjusted odds ratio with a 95% confidence interval was used and statistical significance was declared at P-value < 0.05.

Results:

The study revealed that rural residence (adjusted odds ratio = 3, 95% confidence interval = 1.25–7.21), having no history of stillbirth (adjusted odds ratio = 4.2, 95% confidence interval = 1.20–14.62), prior vaginal birth after cesarean (adjusted odds ratio = 2.4, 95% confidence interval = 1.2–6.4), counseling about a trial of labor after cesarean during antenatal follow-up (adjusted odds ratio = 4.7, 95% confidence interval = 1.88–11.74), and birth interval of >2 years (adjusted odds ratio = 8.9, 95% confidence interval = 3.25–24.67) were found to be determinants of successful vaginal birth after cesarean.

Conclusion:

Place of residence, history of stillbirth, history of vaginal birth after cesarean, counseling about mode of delivery during antenatal care, and birth interval were determinants of successful trial of labor after cesarean. Given these factors, it is recommended that care providers should advocate delaying pregnancy for at least 2 years and counseling women about trial of labor after cesarean during antenatal care follow-up.

A comparison of antenatal prediction models for vaginal birth after caesarean section

ABSTRACT Introduction: An antenatal scoring system for vaginal birth after caesarean section (VBAC) categorises patients into a low or high probability of successful vaginal delivery. It enables counselling and preparation before labour starts. The current study aims to evaluate the role of Grobman nomogram and the Kalok scoring system in predicting VBAC success in Singapore. Methods: This is a retrospective study on patients of gestational age 37 weeks 0 day to 41 weeks 0 day who underwent a trial of labour after 1 caesarean section between September 2016 and September 2017 was conducted. Two scoring systems were used to predict VBAC success, a nomogram by Grobman et al. in 2007 and an additive model by Kalok et al. in 2017. Results: A total of 190 patients underwent a trial of labour after caesarean section, of which 103 (54.2%) were successful. The Kalok scoring system (AUC [area under the curve] 0.740) was a better predictive model than Grobman nomogram (AUC 0.664). Patient’s age odds ratio [OR] 0.915, 95% CI [confidence interval] 0.844–0.992), body mass index at booking (OR 0.902, 95% CI 0.845–0.962), and history of successful VBAC (OR 4.755, 95% CI 1.248–18.120) were important factors in predicting VBAC. Conclusion: Neither scoring system was perfect in predicting VBAC among local women. Further customisation of the scoring system to replace ethnicity with the 4 races of Singapore can be made to improve its sensitivity. The factors identified in this study serve as a foundation for developing a population-specific antenatal scoring system for Singapore women who wish to have a trial of VBAC. Keywords: Antenatal scoring system, caesarean section, obstetrics and gynaecology, trial of labour after caesarean section, vaginal birth after caesarean section

Factors associated with the outcome of TOLAC after one previous caesarean section: a retrospective cohort study

The factors associated with the outcome of trial of labour after one previous Caesarean Section; a retrospective cohort study. A retrospective observational study was performed on all eligible consecutive singleton pregnancies planned for trial of labour after one previous Caesarean Section (TOLAC) over a period of 18 months to study the success rate of vaginal birth after Caesarean Section (VBAC) and to find out the factors associated with successful and failed TOLAC. All of the data were entered in electronic format and the data was analysed in detail. Of the 1324 women studied, the VBAC rate was 65.3% and the incidence of scar rupture was 0.5%. The composite adverse maternal (postpartum haemorrhage and intensive care admission) and foetal outcome (still birth, 5-minute APGAR <7 and NICU admission) was more in the failed TOLAC group. Various demographic, clinical and obstetric factors were studied in detail between the successful and failed TOLAC groups. The favourable Bishop Score (>4) was independently associated with successful TOLAC (OR 4.3; 95% CI 3.3-5.6 p < .001). Maternal age of >30 years, (OR 0.57; 95% CI 0.41-0.79; p = .001), labour induction (OR 0.43; 95% CI 0.33-0.56; p < .001) and estimated foetal weight of >3500 g (0.31; 95% CI 0.14-0.6; p = .002) were the factors independently associated with failed TOLAC. Previous indication for a Caesarean Section and previous vaginal delivery were not found to be independently associated with the outcome of TOLAC. The predictive models for TOLAC need to be used cautiously and the risk assessment should be done on an individual basis.IMPACT STATEMENTWhat is already known on this subject? TOLAC is a reasonable strategy in Obstetrics especially after one Caesarean Section to minimise the morbidity associated with rising Caesarean Section. However, the maternal and foetal morbidity are more following unsuccessful TOLAC. The factors which predict the outcome of TOLAC are multifactorial which include maternal demographic factors, previous obstetric factors like indication for Caesarean Section, intraoperative complications, inter-pregnancy interval, current obstetric factors such as gestational age, Bishop Score before delivery, labour factors and foetal factors, e.g. sex and foetal size.What do the results of this study add? We tried to include all the possible factors which probably influence TOLAC and found only Bishop Score, maternal age, foetal size and labour induction were the factors independently associated with the outcome of TOLAC. A Bishop Score of >4 admission was the greatest predictor of successful TOLAC (OR 4.3). Similarly, labour induction and foetal size of >3.5 kg were associated with 60% and 70% less chance of VBAC, respectively.What are the implications of these findings for clinical practice and/or further research? The factors found to be associated with successful and failed TOLAC may be utilised to develop a predictive model. More so, prospective studies are needed to test such predictive models.

Development and Validation of Predictive Models for Vaginal Birth After Cesarean Delivery in China

Background

The rate of delivery by cesarean section is rising in China, where vaginal birth after cesarean (VBAC) is in its early stages. There are no validated screening tools to predict VBAC success in China. The objective of this study was to identify the variables predicting the likelihood of successful VBAC to create a predictive model.

Material/Methods

This multicenter, retrospective study included 1013 women at ≥28 gestational weeks with a vertex singleton gestation and 1 prior low-transverse cesarean from January 2017 to December 2017 in 11 public tertiary hospitals within 7 provinces of China. Two multivariable logistic regression models were developed: (1) at a first-trimester visit and (2) at the pre-labor admission to hospital. The models were evaluated with the area under the receiver operating characteristic curve (AUC) and internally validated using k-fold cross-validation. The pre-labor model was calibrated and a graphic nomogram and clinical impact curve were created.

Results

A total of 87.3% (884/1013) of women had successful VBAC, and 12.7% (129/1013) underwent unplanned cesarean delivery after a failed trial of labor. The AUC of the first-trimester model was 0.661 (95% confidence interval [CI]: 0.61–0.712), which increased to 0.758 (95% CI: 0.715–0.801) in the pre-labor model. The pre-labor model showed good internal validity, with AUC 0.743 (95% CI: 0.694–0.785), and was well calibrated.

Conclusions

VBAC provides women the chance to experience a vaginal delivery. Using a pre-labor model to predict successful VBAC is feasible and may help choose mode of birth and contribute to a reduction in cesarean delivery rate.

Prediction of vaginal birth after cesarean delivery in Southeast China: a retrospective cohort study

BACKGROUND

We aimed to develop and validate a nomogram for effective prediction of vaginal birth after cesarean (VBAC) and guide future clinical application.

METHODS

We retrospectively analyzed data from hospitalized pregnant women who underwent trial of labor after cesarean (TOLAC), at the Fujian Provincial Maternity and Children's Hospital, between October 2015 and October 2017. Briefly, we included singleton pregnant women, at a gestational age above 37 weeks who underwent a primary cesarean section, in the study. We then extracted their sociodemographic data and clinical characteristics, and randomly divided the samples into training and validation sets. We employed the least absolute shrinkage and selection operator (LASSO) regression to select variables and construct VBAC success rate in the training set. Thereafter, we validated the nomogram using the concordance index (C-index), decision curve analysis (DCA), and calibration curves. Finally, we adopted the Grobman's model to perform comparisons with published VBAC prediction models.

RESULTS

Among the 708 pregnant women included according to inclusion criteria, 586 (82.77%) patients were successfully for VBAC. Multivariate logistic regression models revealed that maternal height (OR, 1.11; 95% CI, 1.04 to 1.19), maternal BMI at delivery (OR, 0.89; 95% CI, 0.79 to 1.00), fundal height (OR, 0.71; 95% CI, 0.58 to 0.88), cervix Bishop score (OR, 3.27; 95% CI, 2.49 to 4.45), maternal age at delivery (OR, 0.90; 95% CI, 0.82 to 0.98), gestational age (OR, 0.33; 95% CI, 0.17 to 0.62) and history of vaginal delivery (OR, 2.92; 95% CI, 1.42 to 6.48) were independently associated with successful VBAC. The constructed predictive model showed better discrimination than that from the Grobman's model in the validation series (c-index 0.906 VS 0.694, respectively). On the other hand, decision curve analysis revealed that the new model had better clinical net benefits than the Grobman's model.

CONCLUSIONS

VBAC will aid in reducing the rate of cesarean sections in China. In clinical practice, the TOLAC prediction model will help improve VBAC's success rate, owing to its contribution to reducing secondary cesarean section.