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Applying machine-learning models to successful vaginal birth after two cesareans.

Rachel S Griffin1, Emanuelle Hay2, Itai Braude3

  • 1Department of Obstetrics and Gynecology, Laniado Medical Center, Netanya, Israel - rasoussan@gmail.com.

Minerva Obstetrics and Gynecology
|June 11, 2026
PubMed
Summary

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Vaginal birth after two cesarean deliveries (VBAC2) is achievable for many women, with success rates of 78.9%. Key predictors for successful VBAC2 include the time since the last C-section and cervical dilation.

Area of Science:

  • Obstetrics and Gynecology
  • Reproductive Medicine
  • Maternal-Fetal Medicine

Background:

  • Vaginal birth after two cesarean deliveries (VBAC2) is a growing consideration for women.
  • While VBAC2 is feasible, especially in grand multiparous women, predictors of success and risk reduction are not fully understood.
  • Identifying factors for safe VBAC2 is crucial for informed delivery decisions.

Purpose of the Study:

  • To identify predictors of successful vaginal birth after two cesarean deliveries (VBAC2).
  • To evaluate the safety and success rates of VBAC2 in a large cohort.
  • To apply machine learning models for predicting VBAC2 outcomes.

Main Methods:

  • A retrospective observational study of 541 women with two prior cesarean deliveries attempting VBAC2.

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  • Machine learning models (XGBoost Classifier) were used to predict VBAC2 success and safety.
  • Primary outcome: successful VBAC2 without uterine rupture; secondary outcomes: Apgar score, NICU admission, postpartum transfusion.

    • Main Results:

    • 78.9% of women achieved a successful VBAC2, with a uterine rupture rate of 2.0%.
    • The XGBoost Classifier demonstrated 83% sensitivity in predicting successful VBAC2.
    • Significant predictors of VBAC2 success included time since last cesarean, prior vaginal births, and cervical dilation.

    Conclusions:

    • Grand multiparous women exhibit higher VBAC2 success rates with low uterine rupture risk.
    • Machine learning models effectively predict the likelihood of safe VBAC2, aiding clinical decision-making.
    • Prior vaginal birth and cervical dilation are key factors influencing VBAC2 success.