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Predicting successful vaginal birth after Cesarean section using a model based on Cesarean scar features examined by
1Obstetrics and Gynaecology Unit, Queen Charlottes and Chelsea Hospital, Imperial College, London, UK.
Objective:
To develop a model to predict the success of a trial of vaginal birth after Cesarean section (VBAC) based on sonographic measurements of Cesarean section (CS) scar features, demographic variables and previous obstetric history.
Methods:
We used transvaginal sonography (TVS) to examine the CS scar of 320 consecutive pregnant women. TVS was carried out at 11-13, 19-21 and 34-36 weeks' gestation and prospective measurements of the scar were recorded at each visit according to a defined protocol. A logistic regression model to predict success of VBAC was developed for those patients with a visible scar on ultrasound and only one previous CS. The model was evaluated using bootstrap validation.
Results:
There were 131 women with one previous CS and a visible scar, of whom 10 underwent CS prior to labor and were excluded from analysis. Successful VBAC was achieved in 74/121 (61%) of the remaining cases. The prediction model developed was based on patient age, previous history of VBAC, residual myometrial thickness (RMT) and the change in RMT from the first to the second trimester (ΔRMT). The internally validated area under the receiver-operating characteristics curve was 0.62 when measurements of RMT and ΔRMT were excluded, but 0.94 when scar information was incorporated into the model.
Conclusion:
Ultrasound measurements of CS scar, namely RMT and the change in RMT from the first to the second trimester of pregnancy, when incorporated into a mathematical model, can predict accurately a successful trial of labor in patients with one previous CS.
