Vaginal birth after caesarean section prediction models: a UK comparative observational study

Area of Science:

• Obstetrics and Gynecology
• Maternal-Fetal Medicine
• Health Services Research

Background:

• Trial of labour after one previous lower segment caesarean section (TOLAC) is a common obstetric procedure.
• Predicting successful vaginal birth after cesarean (VBAC) is crucial for maternal and infant outcomes.
• Accurate prediction models can support shared decision-making between clinicians and patients.

Purpose of the Study:

• To evaluate the performance of three statistical models in predicting successful VBAC.
• To validate the most accurate models in a UK antenatal population.

Main Methods:

• Retrospective observational study using the Northern Ireland Maternity Service Database (NIMats).
• Included 385 women undergoing TOLAC between 2010-2012.
• Area Under the Curve (AUC) and correlation analysis were used to assess model performance.

Main Results:

• The Smith et al. model (AUC=0.74) and Grobman et al. model (AUC=0.72) demonstrated the best predictive performance.
• Both models showed good fit with observed outcomes, validating their use in the study population.
• The Smith et al. model identified distinct risk groups for cesarean delivery.

Conclusions:

• The Smith et al. and Grobman et al. models are suitable for use in the UK.
• These validated models can empower women with information to make informed choices regarding delivery after a prior cesarean section.