Cervical length measured before delivery and the success rate of vaginal birth after cesarean (VBAC)

Abstract 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.

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Examining the validity of a predictive model for vaginal birth after cesarean

Journal of Perinatal Medicine ◽

10.1515/jpm-2019-0345 ◽

2019 ◽

Vol 48 (1) ◽

pp. 11-15

Author(s):

Jennifer W.H. Wong ◽

Kurt D.N. Yoshino ◽

Hyeong Jun Ahn ◽

So Yung Choi ◽

Ann L. Chang

Keyword(s):

Success Rate ◽

Operating Characteristic ◽

Characteristic Curve ◽

Vaginal Birth ◽

Success Rates ◽

Vaginal Birth After Cesarean ◽

Single Institution ◽

Maternal Fetal Medicine ◽

Cesarean Deliveries ◽

Operating Characteristic Curve

AbstractBackgroundThe Maternal-Fetal Medicine Units (MFMU) vaginal birth after cesarean (VBAC) calculator, while accurate for candidates with high predicted success rates, is not as accurate for poor candidates. This study examines the calculator’s validity in an understudied multiracial cohort with a high proportion of poor candidates.MethodsThis retrospective study examined women with one or two prior cesarean deliveries who attempted VBAC at a single institution. Subjects were placed into quartiles based on MFMU-predicted success rates. For each quartile, actual and predicted success rates were compared. The calculated area under the receiver operating characteristic curve (AUC) was compared to the original AUC.ResultsThe study included 1604 women. Actual and predicted VBAC rates were similar in the lowest and highest quartile groups, 18.2% vs. 21.2% (n = 11, P > 0.99) and 87.1% vs. 88.5% (n = 1090, P = 0.14), respectively. In the 51–75% predicted success rate group, the actual VBAC rate was higher than the predicted rate, 69.9% vs. 65.5% (n = 394) but not statistically significant (P = 0.07). In the 25–50% predicted success rate group, the actual VBAC rate was significantly higher than the predicted rate 55.1% vs. 39.6% (n = 109, P = 0.002). The actual AUC was lower than the MFMU model, 0.72 [95% confidence interval (CI) 0.69–0.75] vs. 0.77 (95% CI 0.76–0.78) (P < 0.001).ConclusionThe MFMU VBAC calculator’s predicted success rates were comparable to actual success rates for candidates with predicted success rates >75%. As predicted success rates declined, the calculator was increasingly inaccurate and underestimated the success rate. Caution should be taken when using the MFMU VBAC calculator for poor candidates.

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Second Trimester Cervical Length and Its Association with Vaginal Birth after Cesarean Delivery

American Journal of Perinatology ◽

10.1055/s-0035-1554796 ◽

2015 ◽

Vol 33 (01) ◽

pp. 020-023 ◽

Cited By ~ 1

Author(s):

Kelly Orzechowski ◽

Vincenzo Berghella ◽

Jason Baxter ◽

Sara Nicholas

Keyword(s):

Cesarean Delivery ◽

Cervical Length ◽

Vaginal Birth ◽

Second Trimester ◽

Vaginal Birth After Cesarean

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

American Journal of Perinatology Reports ◽

10.1055/s-0037-1599129 ◽

2017 ◽

Vol 07 (01) ◽

pp. e31-e38 ◽

Cited By ~ 13

Author(s):

Melanie Maykin ◽

Amanda Mularz ◽

Lydia Lee ◽

Stephanie Valderramos

Keyword(s):

Prediction Model ◽

Success Rate ◽

Cesarean Delivery ◽

Ethnically Diverse ◽

Vaginal Birth ◽

Success Rates ◽

Vaginal Birth After Cesarean ◽

Maternal Fetal Medicine ◽

Trial Of Labor ◽

Network Prediction

Objective To investigate the validity of a prediction model for success of vaginal birth after cesarean delivery (VBAC) in an ethnically diverse population. Methods We performed a retrospective cohort study of women admitted at a single academic institution for a trial of labor after cesarean from May 2007 to January 2015. Individual predicted success rates were calculated using the Maternal–Fetal Medicine Units Network prediction model. Participants were stratified into three probability-of-success groups: low (<35%), moderate (35–65%), and high (>65%). The actual versus predicted success rates were compared. Results In total, 568 women met inclusion criteria. Successful VBAC occurred in 402 (71%), compared with a predicted success rate of 66% (p = 0.016). Actual VBAC success rates were higher than predicted by the model in the low (57 vs. 29%; p < 0.001) and moderate (61 vs. 52%; p = 0.003) groups. In the high probability group, the observed and predicted VBAC rates were the same (79%). Conclusion When the predicted success rate was above 65%, the model was highly accurate. In contrast, for women with predicted success rates <35%, actual VBAC rates were nearly twofold higher in our population, suggesting that they should not be discouraged by a low prediction score.

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