Antenatal counseling for patients with one prior low-transverse cesarean section (LTCS) contemplating Trial of Labor After Cesarean (TOLAC).
Standardizing shared decision-making regarding mode of delivery at 37 0/7 to 41 6/7 weeks gestation.
Informing patients of their individualized probability of successful vaginal birth versus repeat cesarean.
Patient Selection
Single prior low-transverse uterine incision.
Singleton pregnancy.
Cephalic presentation.
Term gestation (≥37 weeks).
Absolute Contraindications to TOLAC
Do not use this calculator or attempt TOLAC if: Prior classical or T-shaped uterine incision, prior uterine rupture, extensive transfundal uterine surgery (e.g., myomectomy), or any standard contraindication to vaginal delivery (e.g., placenta previa).
Section 2
Formula & Logic
Scoring Variables (2021 Race-Neutral Model)
Maternal Age
Continuous variable
BMI
Calculated from height & pre-pregnancy weight
Prior Vaginal Delivery
None vs. Pre-CS vs. Post-CS (VBAC)
Prior Arrest Disorder
Yes/No (Indication for prior CS)
Chronic Hypertension
Yes/No
Physiological Rationale
The model utilizes a logistic regression equation. Prior vaginal delivery is the strongest positive predictor of success, reflecting a "proven" pelvis. Conversely, a prior CS performed for an arrest disorder (failure to progress or fail to descend) suggests a recurring mechanical or physiological barrier, reducing the likelihood of success in subsequent trials.
The "Race-Neutral" Update
The 2021 revision (Grobman et al.) removed race and ethnicity as variables. The updated model provides similar predictive accuracy (AUC 0.71) without codifying social constructs as biological determinants, addressing historical disparities where Black and Hispanic patients were assigned lower success probabilities.
Section 3
Pearls/Pitfalls
Critical Insights
Prior VBAC is the single best predictor of future success (rates often >90%).
The calculator is most accurate for patients who enter labor spontaneously.
A success probability of >60-70% is generally considered "favorable" for a trial of labor.
Limitations & Caveats
Does not account for induction of labor — induction reduces success rates by ~10-15% compared to spontaneous labor.
Estimated fetal weight (EFW) > 4000g decreases probability of success but is not a variable in this specific model.
Section 4
Next Steps
Favorable Probability (>70%)
01
Counsel patient on the high likelihood of successful vaginal delivery.
02
Discuss the benefit-risk ratio: Lower maternal morbidity compared to repeat CS if successful.
03
Document shared decision-making for TOLAC.
04
Ensure facility allows for "immediate" emergency CS should rupture occur.
Uterine Rupture Risk (TOLAC vs. ERCD)
TOLAC (Success)
Risk of rupture: ~0.5% (1 in 200)
TOLAC (Failure)
Maternal morbidity increases significantly
Induction of Labor
Increases rupture risk by 2x to 3x
Spontaneous Labor
Lowest risk profile for TOLAC
The "Danger Zone"
The risk of uterine rupture is significantly higher if the prior cesarean was performed less than 18 months ago, or if prostaglandins (misoprostol) are used for induction.
Unfavorable/Low Probability (<60%)
01
Counsel patient that while VBAC is still possible, the risk of "failed" TOLAC is higher.
02
Explain that a failed TOLAC (maternal morbidity) is riskier than a scheduled repeat CS.
03
Consider Elective Repeat Cesarean Delivery (ERCD) if the patient prioritizes avoiding labor or failed trial.
Related Tools
Bishop Score
Pregnancy Weight Gain Calculator
Estimated Date of Delivery (EDD)
Section 5
Evidence Appraisal
Foundational Model
Development of a nomogram for prediction of vaginal birth after cesarean delivery.
Grobman WA et al. • Obstet Gynecol.. 2007;Initial MFMU (Maternal-Fetal Medicine Units Network) derivation study. n = 15,515 patients. Established the core predictors for VBAC success.
Race-Neutral Validation
Prediction of Vaginal Birth After Cesarean Delivery in North America: A Race-Neutral Algorithm.
Grobman WA et al. • Obstet Gynecol.. 2021;Updated the algorithm to remove race/ethnicity, showing that the model maintained predictive performance while eliminating bias.
Guideline Reference
ACOG Practice Bulletin No. 205 (Vaginal Birth After Cesarean Delivery) recommends the use of validated scoring systems like this MFMU model to assist in counseling and shared decision-making.
Section 6
Literature
The MFMU Network
The Maternal-Fetal Medicine Units (MFMU) Network was established by the NICHD to conduct large-scale clinical trials in obstetrics. This calculator is the result of massive multi-center data collection aimed at reducing the rising primary cesarean rate in the US.
Dr. William Grobman
A leading figure in MFM and obstetric health services research. Dr. Grobman championed the removal of race from clinical algorithms to ensure that evidence-based tools do not inadvertently reinforce health inequities.
