Vaginal birth after a caesarean section: the development of a Western European population-based prediction model for deliveries at term.

OBJECTIVE: To develop and internally validate a model that predicts the outcome of an intended vaginal birth after caesarean (VBAC) for a Western European population that can be used to personalise counselling for deliveries at term. DESIGN: Registration-based retrospective cohort study. SETTING: Five university teaching hospitals, seven non-university teaching hospitals, and five non-university non-teaching hospitals in the Netherlands. POPULATION: A cohort of 515 women with a history of one caesarean section and a viable singleton pregnancy, without a contraindication for intended VBAC, who delivered at term. METHODS: Potential predictors for a vaginal delivery after caesarean section were chosen based on literature and expert opinions. We internally validated the prediction model using bootstrapping techniques. MAIN OUTCOME MEASURES: Predictors for VBAC. For model validation, the area under the receiver operating characteristic curve (AUC) for discriminative capacity and calibration-per-risk-quantile for accuracy were calculated. RESULTS: A total of 371 out of 515 women had a VBAC (72%). Variables included in the model were: estimated fetal weight greater than the 90(th) percentile in the third trimester; previous non-progressive labour; previous vaginal delivery; induction of labour; pre-pregnancy body mass index; and ethnicity. The AUC was 71% (95% confidence interval, 95% CI = 69-73%), indicating a good discriminative ability. The calibration plot shows that the predicted probabilities are well calibrated, especially from 65% up, which accounts for 77% of the total study population. CONCLUSION: We developed an appropriate Western European population-based prediction model that is aimed to personalise counselling for term deliveries.

Involving women in personalised decision-making on mode of delivery after caesarean section: the development and pilot testing of a patient decision aid.

OBJECTIVE: To develop a patient decision aid (PtDA) for mode of delivery after caesarean section that integrates personalised prediction of vaginal birth after caesarean (VBAC) with the elicitation of patient preferences and evidence-based information. DESIGN: A PtDA was developed and pilot tested using the International Patients Decision Aid Standards (IPDAS) criteria. SETTING: Obstetric health care in the Netherlands. POPULATION: A multidisciplinary steering group, an expert panel, and 25 future users of the PtDA, i.e. women with a previous caesarean section. METHODS: The development consisted of a construction phase (definition of scope and purpose, and selection of content, framework, and format) and a pilot testing phase by interview. The process was supervised by a multidisciplinary steering group. MAIN OUTCOME MEASURES: Usability, clarity, and relevance. RESULTS: The construction phase resulted in a booklet including unbiased balanced information on mode of birth after caesarean section, a preference elicitation exercise, and tailored risk information, including a prediction model for successful VBAC. During pilot testing, visualisation of risks and clarity formed the main basis for revisions. Pilot testing showed the availability of tailored structured information to be the main factor involving women in decision-making. The PtDA meets 39 out of 50 IPDAS criteria (78%): 23 out of 23 criteria for content (100%) and 16 out of 20 criteria for the development process (80%). Criteria for effectiveness (n = 7) were not evaluated. CONCLUSIONS: An evidence-based PtDA was developed, with the probability of successful VBAC and the availability of structured information as key items. It is likely that the PtDA enhances the quality of decision-making on mode of birth after caesarean section.

Predicting successful intended vaginal delivery after previous caesarean section: external validation of two predictive models in a Dutch nationwide registration-based cohort with a high intended vaginal delivery rate.

OBJECTIVE: To externally validate two models from the USA (entry-to-care [ETC] and close-to-delivery [CTD]) that predict successful intended vaginal birth after caesarean (VBAC) for the Dutch population. DESIGN: A nationwide registration-based cohort study. SETTING: Seventeen hospitals in the Netherlands. POPULATION: Seven hundred and sixty-three pregnant women, each with one previous caesarean section and a viable singleton cephalic pregnancy without a contraindication for an intended VBAC. METHODS: The ETC model comprises the variables maternal age, prepregnancy body mass index (BMI), ethnicity, previous vaginal delivery, previous VBAC and previous nonprogressive labour. The CTD model replaces prepregnancy BMI with third-trimester BMI and adds estimated gestational age at delivery, hypertensive disease of pregnancy, cervical examination and induction of labour. We included consecutive medical records of eligible women who delivered in 2010. For validation, individual probabilities of women who had an intended VBAC were calculated. MAIN OUTCOME MEASURES: Discriminative performance was assessed with the area under the curve (AUC) of the receiver operating characteristic and predictive performance was assessed with calibration plots and the Hosmer-Lemeshow (H-L) statistic. RESULTS: Five hundred and fifteen (67%) of the 763 women had an intended VBAC; 72% of these (371) had an actual VBAC. The AUCs of the ETC and CTD models were 68% (95% CI 63-72%) and 72% (95% CI 67-76%), respectively. The H-L statistic showed a P-value of 0.167 for the ETC model and P = 0.356 for the CTD model, indicating no lack of fit. CONCLUSION: External validation of two predictive models developed in the USA revealed an adequate performance within the Dutch population.