Prediction Of Vaginal Birth Research Articles

Accuracy of sonographic lower segment thickness and prediction of vaginal birth after caesarean in a resourced-limited setting; Prospective study.

To assess the accuracy of ultrasound measurement of the lower uterine segment (LUS) thickness against findings at laparotomy, and to investigate its correlation with the success rate of vaginal birth after one previous caesarean delivery (CD) in a resource-limited setting. Prospective study. Obstetrics and Gynaecology department in a tertiary hospital in Ghana. Women with one previous CD undergoing either a trial of labour (TOLAC) or elective CD. Myometrial lower uterine segment thickness (mLUS) and full lower uterine segment thickness (fLUS) were measured with transvaginal ultrasound (TVUS). The women were managed according to local protocols with the clinicians blinded to the ultrasound measurements. The LUS was measured intraoperatively for comparison with ultrasound measurements. Lower uterine segment findings at laparotomy, successful vaginal birth. A total of 311 pregnant women with one previous CD were enrolled; 147 women underwent elective CD and 164 women underwent a TOLAC. Of the women that underwent TOLAC, 96 (58.5%) women had a successful vaginal birth. The mLUS was comparable to the intraoperative measurement in the elective CD group with LUS thickness <5 mm (bias of 0.01, 95% CI -0.10 to 0.12 mm) whereas fLUS overestimated LUS <5 mm (bias of 0.93, 95% CI 0.80-1.06 mm). Successful vaginal birth rate correlated with increasing mLUS values (odds ratio 1.30, 95% CI 1.03-1.64). Twelve cases of uterine defect were recorded. LUS measurement ≤2.0 mm was associated with an increased risk of uterine defects with a sensitivity of 91.7% (95% CI 61.5-99.8%) and specificity of 81.8% (95% CI 75.8-86.8%). Accurate TVUS measurement of the LUS is technically feasible in a resource-limited setting. This approach could help in making safer decisions on mode of birth in limited-resource settings.

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

BackgroundA 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. ObjectiveTo 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. MethodsIn 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. ResultsThis 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). ConclusionsWe 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.

Prediction of vaginal birth after cesarean in China.

This study aimed to develop and validate a prediction model of vaginal birth after cesarean delivery (VBAC) in China. A nomogram for effective prediction of VBAC of singleton, cephalic and one previous low-transverse cesarean section deliveries was created by comparing the combinations of ultrasonographic and non-ultrasonographic factors from five hospitals between 2018 and 2019. A total of 1066 women were included. Of the women who underwent trial of labor after cesarean (TOLAC), 854 (80.1%) had a VBAC. Ultrasound factors included reached a higher area under the curve (AUC) combined with non-ultrasonographic factors. Of the three ultrasonographic factors analyzed, the best predictive factor for successful TOLAC was fetal abdominal circumference. A nomogram was generated with eight validated factors, including maternal age, gestational week, height, previous vaginal delivery, Bishop score, dilatation of the cervix at the time of admission, body mass index at delivery, and fetal abdominal circumference by ultrasound. The trained and validated AUC were 0.719 (95% confident interval 0.674-0.764) and 0.774 (95% confident interval 0.712-0.837), respectively. Our VBAC nomogram based on obstetric factors and fetal abdominal circumference obtained by ultrasound could be used to counsel women who are considering TOLAC.

Prediction of vaginal birth after cesarean for labor dystocia by sonographic estimated fetal weight.

To estimate the association of the weight difference between the index trial of labor after cesarean (TOLAC) sonographic estimated fetal weight (sEFW) and prior delivery birth weight with TOLAC success rate among women with previous labor dystocia and no prior vaginal delivery. A retrospective cohort study including all women with prior cesarean for labor dystocia and no prior vaginal delivery undergoing TOLAC during between March 2011 and June 2020 with a sEFW within 1week from delivery. Overall, 168 women were included, of those 107 (63.7%) successfully delivered vaginally. The mean sEFW and mean birth weight were lower in the TOLAC success group (P=0.010 and P=0.013, respectively). The rate of higher sEFW in the current delivery compared with the previous delivery did not differ between study groups. The rate of higher TOLAC birth weight was lower in the TOLAC success group (odds ratio 0.30; 95% confidence interval 0.15-0.58). In multivariable regression analysis, maternal age older than 30years, induction of labor, and higher birth weight were independently negatively associated with TOLAC success (adjusted odds ratio [95% confidence interval]: 0.27 [0.10-0.70], 0.27 [0.08-0.90], and 0.43 [0.19-0.94]; P=0.008, P=0.034, and P=0.035, respectively). sEFW characteristics did not predict the success or failure of TOLAC among women with prior labor dystocia and no previous vaginal delivery.

Prediction of vaginal birth after cesarean delivery in term gestations: a calculator without race and ethnicity

Investigators have attempted to derive tools that could provide clinicians with an easily obtainable estimate of the chance of vaginal birth after cesarean delivery for those who undertake trial of labor after cesarean delivery. One tool that has been validated externally was derived from data from the Maternal-Fetal Medicine Units Cesarean Registry. However, concern has been raised that this tool includes the socially constructed variables of race and ethnicity. This study aimed to develop an accurate tool to predict vaginal birth after cesarean delivery, using data easily obtainable early in pregnancy, without the inclusion of race and ethnicity. This was a secondary analysis of the Cesarean Registry of the Maternal-Fetal Medicine Units Network. The approach to the current analysis is similar to that of the analysis in which the previous vaginal birth after cesarean delivery prediction tool was derived. Specifically, individuals were included in this analysis if they were delivered on or after 37 0/7 weeks' gestation with a live singleton cephalic fetus at the time of labor and delivery admission, had a trial of labor after cesarean delivery, and had a history of 1 previous low-transverse cesarean delivery. Information was only considered for inclusion in the model if it was ascertainable at an initial prenatal visit. Model selection and internal validation were performed using a cross-validation procedure, with the dataset randomly and equally divided into a training set and a test set. The training set was used to identify factors associated with vaginal birth after cesarean delivery and build the logistic regression predictive model using stepwise backward elimination. A final model was generated that included all variables found to be significant (P<.05). The accuracy of the model to predict vaginal birth after cesarean delivery was assessed using the concordance index. The independent test set was used to estimate classification errors and validate the model that had been developed from the training set, and calibration was assessed. The final model was then applied to the overall analytical population. Of the 11,687 individuals who met the inclusion criteria for this secondary analysis, 8636 (74%) experienced vaginal birth after cesarean delivery. The backward elimination variable selection yielded a model from the training set that included maternal age, prepregnancy weight, height, indication for previous cesarean delivery, obstetrical history, and chronic hypertension. Vaginal birth after cesarean delivery was significantly more likely for women who were taller and had a previous vaginal birth, particularly if that vaginal birth had occurred after a previous cesarean delivery. Conversely, vaginal birth after cesarean delivery was significantly less likely for women whose age was older, whose weight was heavier, whose indication for previous cesarean delivery was arrest of dilation or descent, and who had a history of medication-treated chronic hypertension. The model had excellent calibration between predicted and empirical probabilities and, when applied to the overall analytical population, an area under the receiver operating characteristic curve of 0.75 (95% confidence interval, 0.74-0.77), which is similar to the area under the receiver operating characteristic curve of the previous model (0.75) that included race and ethnicity. We successfully derived an accurate model (available at https://mfmunetwork.bsc.gwu.edu/web/mfmunetwork/vaginal-birth-after-cesarean-calculator), which did not include race or ethnicity, for the estimation of the probability of vaginal birth after cesarean delivery.

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

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

Inter-delivery Time Interval and the Likelihood of Successful Vaginal Birth After Cesarean Delivery [21P

INTRODUCTION: The most commonly utilized prediction models to assist in the prediction of vaginal birth after cesarean delivery (VBAC) have not included inter-delivery time interval as a contributing variable. Therefore, we sought to determine the association of inter-delivery time interval and rate of successful VBAC. METHODS: This retrospective cohort study utilized the United States Natality Live Births database from the Center for Disease Control and Prevention for the years 2016–2017. Singleton patients at term with their second pregnancy and live birth undergoing a trial of labor after one prior cesarean delivery (TOLAC) were eligible for inclusion. The inter-delivery time interval, defined as the time elapsed between live births, was divided into 7 groups by months: 12–17, 18–23, 24–35, 36–47, 48–59, 60–71, 72 and beyond. Pearson's Chi-Squared test was used to compare rates of successful VBAC across the different inter-delivery time interval groups. Statistical significance was determined as P&lt;.05. RESULTS: Of the 60,526 women who underwent TOLAC, 39,948 (66%) had a VBAC. The highest rate of VBAC success was seen with an inter-delivery time interval of 24 to 35 months (12,368/17,760; 69.6%). The differences in rates of VBAC between the different time intervals were statistically significant (P&lt;.0001). CONCLUSION: Overall, the rate of successful VBAC in the United States among cases from 2016–2017 was 66%. Our data indicate that the rate of successful VBAC is affected by the inter-delivery time interval, with the optimal time for VBAC being 24–35 months after cesarean delivery. The clinical implication of this statistical finding requires further study.

Prediction of vaginal birth after cesarean deliveries using machine learning

Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliveries. Complication rates are lowest when a vaginal birth is achieved and highest when an unplanned cesarean delivery is performed, which emphasizes the need to assess, in advance, the likelihood of a successful vaginal birth after cesarean delivery. Vaginal birth after cesarean delivery calculators have been developed in different populations; however, some limitations to their implementation into clinical practice have been described. Machine-learning methods enable investigation of large-scale datasets with input combinations that traditional statistical analysis tools have difficulty processing. The aim of this study was to evaluate the feasibility of using machine-learning methods to predict a successful vaginal birth after cesarean delivery. The electronic medical records of singleton, term labors during a 12-year period in a tertiary referral center were analyzed. With the use of gradient boosting, models that incorporated multiple maternal and fetal features were created to predict successful vaginal birth in parturients who undergo a trial of labor after cesarean delivery. One model was created to provide a personalized risk score for vaginal birth after cesarean delivery with the use of features that are available as early as the first antenatal visit; a second model was created that reassesses this score after features are added that are available only in proximity to delivery. A cohort of 9888 parturients with 1 previous cesarean delivery was identified, of which 75.6% of parturients (n=7473) attempted a trial of labor, with a success rate of 88%. A machine-learning-based model to predict when vaginal delivery would be successful was developed. When features that are available at the first antenatal visit are used, the model showed a receiver operating characteristic curve with area under the curve of 0.745 (95% confidence interval, 0.728-0.762) that increased to 0.793 (95% confidence interval, 0.778-0.808) when features that are available in proximity to the delivery process were added. Additionally, for the later model, a risk stratification tool was built to allocate parturients into low-, medium-, and high-risk groups for failed trial of labor after cesarean delivery. The low- and medium-risk groups (42.4% and 25.6% of parturients, respectively) showed a success rate of 97.3% and 90.9%, respectively. The high-risk group (32.1%) had a vaginal delivery success rate of 73.3%. Application of the model to a cohort of parturients who elected a repeat cesarean delivery (n=2145) demonstrated that 31% of these parturients would have been allocated to the low- and medium-risk groups had a trial of labor been attempted. Trial of labor after cesarean delivery is safe for most parturients. Success rates are high, even in a population with high rates of trial of labor after cesarean delivery. Application of a machine-learning algorithm to assign a personalized risk score for a successful vaginal birth after cesarean delivery may help in decision-making and contribute to a reduction in cesarean delivery rates. Parturient allocation to risk groups may help delivery process management.

Prediction of Vaginal Birth after Cesarean Section Using Scoring System at the Time of Admission for Trial of Labor: A One-year Prospective Cohort Study

Prediction of Vaginal Birth after Cesarean Section Using Scoring System at the Time of Admission for Trial of Labor: A One-year Prospective Cohort Study

216: Can prediction of vaginal birth after cesarean at admission for delivery be improved?

The Maternal Fetal Medicine Units (MFMU) Network predictive model for vaginal birth after cesarean (VBAC) was modified by incorporating variables available at delivery to improve accuracy. There is limited evidence describing performance of the “admission model” in populations managed with recommendations from the 2014 Obstetric Care Consensus to extend labor duration. We aimed to explore additional factors associated with VBAC in a population managed with current labor standards. A retrospective cohort study of women undergoing trial of labor after cesarean (TOLAC) at an academic tertiary institution between 2011 and 2018. Term, singleton gestations with one prior cesarean who presented at £6 cm dilation were included. We compared demographics, obstetric and intrapartum variables using Pearson’s chi-square and Student’s t-test between women with successful VBAC and failed TOLAC including delivery after November 2014 to explore differences in VBAC success before and after the 2014 Obstetric Care Consensus. We performed multivariable logistic regression to generate a predictive model for VBAC. A receiver operating characteristic curve was calculated and the area under the curve (AUC) was then compared between our model and that of the MFMU VBAC calculator. 984 patients were included in analysis. Odds ratios and adjusted odds ratios for the final regression model included 12 variables, Table 1. The odds of VBAC was greater following the 2014 Obstetric Care Consensus, aOR 1.49 (95% CI 1.09 – 2.05). While certain variables in the MFMU admission model remained in the new model, others were either modified for better prediction or excluded. This new model performed more favorably than the MFM-U VBAC calculator in this population, AUC 0.76 (95% CI 0.72 – 0.79) vs. 0.70 (95% CI 0.66 – 0.73), Figure 1. Identification of new and modified variables allowed development of an exploratory model which performed better in our population. The performance of models for VBAC success developed prior to the Obstetric Care Consensus warrants further investigation.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

VBAC: antenatal predictors of success.

To determine antenatal factors that may predict successful vaginal birth after Caesarean section (VBAC), to develop a relevant antenatal scoring system and a nomogram for prediction of vaginal birth after caesarean delivery. A non recurring indication for previous Caesarean section (CS), such as breech presentation or foetal distress, is associated with a much higher successful VBAC rate than recurrent indications, such as cephalopelvic disproportion (CPD). Prior vaginal deliveries are excellent prognostic indicators of successful VBAC, especially if the vaginal delivery follows the prior CS. A low vertical uterine incision does not seem to adversely affect VBAC success rates as compared to a low transverse incision. Maternal obesity and diabetes mellitus adversely affect VBAC outcomes. Foetal macrosomia does not appear to be a contraindication to VBAC, as success rates exceeding 50% are achieved and uterine rupture rates are not increased. An inter-pregnancy interval of <24 months is not associated with a decreased success of VBAC. Success rates decrease when interval increases. Twin gestation does not preclude VBAC. Post-dates pregnancies may deliver successfully by VBAC in greater than two-thirds of cases. There are few absolute contraindications to attempted VBAC. Attempted VBAC will be successful in the majority of attempted cases. (www.actabiomedica.it)

Prediction of vaginal birth after cesarean delivery in Chinese parturients

There is an urgent need in China to better predict vaginal birth after cesarean (VBAC) to face the challenge of the second child policy. We aimed to validate a widely used VBAC prediction model (Grobman’s model) and a modified version of this model in a Chinese population. In this retrospective cohort study, 444 women with one cesarean delivery and at least one subsequent attempt for a trial of labor in Nanjing, China were included. The considered potential VBAC predictors included Grobman’s background variables and five new variables. Overall, a total of 370 women had VBAC, with a success rate of 83.3%. The new background variables “maternal height” and “estimated fetal weight” were considered as two additional predictors for VBAC. The AUC of Grobman’s model was 0.831 (95%CI = 0.775–0.886) while the AUC of our modified model with two new variables added was 0.857 (sensitivity = 72.2%, specificity = 83.8%). However, the difference between the AUC of the two models was not significant (Z = −1.69, P = 0.091). We confirmed that Grobman’s model was accepted in the Chinese population. A modified model that is supplemented with maternal height and estimated fetal weight needs to be further studied in the Chinese population.

Prediction of vaginal birth after one ceasarean delivery for non-progressive labor.

A model exists that predicts the probability of vaginal birth after cesarean (VBAC). That model is not stratified by indication at first cesarean. The aim of the study was to identify factors that may predict successful VBAC in patients operated for arrest of dilatation or descent at their first cesarean. Retrospective analysis of all women with trials of labor after one cesarean (TOLAC) for non-progressive labor between November 2008 and October 2015 was performed (n=231). A multivariate logistic regression analysis was carried out to generate a prediction model for VBAC at hospital admission for planned TOLAC. During the study period, we had 231 parturient women who chose to undergo TOLAC following one previous cesarean delivery for non-progressive labor. Successful VBAC occurred in 155 (67.0%) parturient women. A model consisting of previous successful VBAC, lower head station on decision at previous cesarean delivery, lower newborn weight at previous cesarean delivery and larger cervical effacement on admission at delivery planned for TOLAC correctly classified 75.3% of cases (R 2=0.324, AUC 0.80, 95% CI 0.70-0.89, p<0.001). A predictive model, which incorporates four variables available at hospital admission for the planned TOLAC, has been developed that allows the determination of likelihood of successful VBAC following one cesarean delivery for non-progressive labor.

Insulin-like growth factor binding protein 1, Bishop score, and sonographic cervical length: tolerability and prediction of vaginal birth and vaginal birth within 24 hours following labour induction in nulliparous women

To evaluate the tolerability of cervical insulin-like growth factor binding protein 1 (IGFBP-1) and its value as a predictor of successful labour induction, compared with Bishop score and transvaginal ultrasound (TVUS) cervical length. A prospective study. A tertiary hospital in Malaysia. A cohort of 193 term nulliparous women with intact membranes. Prior to labour induction, cervical fluid was obtained via a vaginal speculum and tested for IGFBP-1, followed by TVUS and finally Bishop score. After each assessment the procedure-related pain was scored from 0 to 10. Cut-off values for Bishop score and cervical length were obtained from the receiver operating characteristic (ROC) curve. Multivariable logistic regression analysis was performed. Vaginal delivery and vaginal delivery within 24 hours of starting induction. Bedside IGFBP-1 testing is better tolerated than Bishop score, but is less well tolerated than TVUS [median (interquartile range) of pain scores: 5 (4-5) versus 6 (5-7) versus 3 (2-3), respectively; P < 0.001]. IGFBP-1 independently predicted vaginal delivery (adjusted odds ratio, AOR 5.5; 95% confidence interval, 95% CI 2.3-12.9) and vaginal delivery within 24 hours of induction (AOR 4.9; 95% CI 2.1-11.6) after controlling for Bishop score (≥4 or ≥5), cervical length (≤29 or ≤27 mm), and other significant characteristics for which the Bishop score and TVUS were not predictive of vaginal delivery after adjustment. IGFBP-1 has 81% sensitivity, 59% specificity, positive and negative predictive values of 82 and 58%, respectively, and positive and negative likelihood ratios of 2.0 and 0.3 for vaginal delivery, respectively. IGFBP-1 better predicted vaginal delivery than BS or TVUS, and may help guide decision making regarding labour induction in nulliparous women. IGFBP-1: a stronger independent predictor of labour induction success than Bishop score or cervical sonography.

Prediction of vaginal birth after cesarean delivery.

To examine factors associated with successful vaginal birth after cesarean (VBAC) and to validate a previously established prediction model. In a retrospective study, data were obtained for women with one prior low-transverse cesarean procedure who underwent a trial of labor with a cephalic singleton pregnancy at term at one UK hospital between January 2000 and August 2013. Univariate analysis and logistic regression analysis were used to identify maternal demographic characteristics significantly associated with successful VBAC and factors independently associated with this outcome, respectively. A prediction model was built, and predicted probabilities were compared with observed frequencies. For validation, probabilities were also calculated by a previous prediction model. Overall, 1463 women formed the cohort. Successful vaginal delivery was achieved in 1050 (71.8%) women. The only factors significantly associated with unsuccessful VBAC were Asian (odds ratio [OR] 1.59, 95% confidence interval [CI] 1.14-2.23) or African (OR 1.80, 95% CI 1.23-2.64) ethnic origin, and previous cesarean for failure to progress (OR 6.39, 95% CI 4.81-8.49). The predicted and observed probability of successful VBAC were well correlated (Spearman ρ, 0.905; P=0.002). The established prediction model was less accurate. Previous cesarean performed for failure to progress and Asian/African ethnic origin were associated with unsuccessful VBAC. The performance of a previous prediction model was inferior.