(Reaffirmed October 2022)
This Practice Advisory was developed by the American College of Obstetricians and Gynecologists’ Committee on Clinical Practice Guidelines—Obstetrics in collaboration with Anjali J. Kaimal, MD, MAS; Aaron B. Caughey, MD, PhD; Manisha Gandhi, MD; Michelle Moniz, MD, MSc; Steven Ralston, MD, MPH; and Jen Villavicencio, MD.
The decision to undergo trial of labor after cesarean (TOLAC) or schedule a repeat cesarean birth is one in which a patient’s values and preferences should be prioritized in a process of shared decision making 1 . While some individuals prioritize the experience of labor in their decision making, the likelihood of a vaginal delivery may also be an important consideration. Pregnant individuals may want to consider the potential risk of complications based on whether a TOLAC results in a vaginal birth after cesarean (VBAC) or cesarean birth 2 . The complexity of this decision-making process and the desire to incorporate information about individual characteristics and obstetric history into counseling prompted the development of calculators to predict the likelihood of VBAC if TOLAC is undertaken. The most widely validated calculator, the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) VBAC Calculator, was published in 2007 and identified age, body mass index, history of vaginal delivery, indication for prior cesarean, history of VBAC, and race and ethnicity as predictors 3 . Given the increasing recognition that differences in outcome by race are not biologically based but rather reflect the impact of systemic racism, social determinants of health, and clinician bias, utilizing race and ethnicity variables in a VBAC calculator may deter patients and clinicians from TOLAC without biologic cause and thereby reinforce inequity rather than support patient-centered care 4 5 .
In recognition of this concern, the investigators who published the original NICHD calculator developed a new calculator utilizing the same dataset collected from 1999 to 2002 without including the socially constructed variables of race and ethnicity 6 . The resulting calculator involves the same variables as the first model with the exception of race and ethnicity and added the variable of chronic hypertension treated with medication before and during pregnancy. Similar to the prior calculator, the calibration curve shows that predictions are more likely to be accurate when the predicted likelihood of VBAC is 60% or higher and deviated substantially when the estimate was 40% or lower 6 7 8 9 10 .
A VBAC calculator is one of many tools that can be used to provide information during a shared-decision-making discussion. When a calculator is used to provide an estimate of the likelihood of a clinical event, the limitations of the tool including uncertainty in the estimate and the impact of unmeasured or excluded clinical characteristics as well as variability in practice patterns must be included to balance the discussion. A VBAC calculator score should not be used as a barrier to TOLAC 11 . This is particularly critical because of the greater likelihood of inaccuracy of the estimate of VBAC for those with lower predicted probabilities 6 7 8 9 10 . Given these limitations, in considering the best way to achieve the shared goal of an informed patient preference, some patients and clinicians may prefer to utilize a calculator while others may prefer a more general discussion of options for mode of delivery, review of overall VBAC rates of 60–80% with TOLAC, and consideration of an individual’s obstetric risk factors along with their preferences and goals 11 12 .
The American College of Obstetricians and Gynecologists (ACOG) is dedicated to reviewing our existing clinical guidance and liaising with stakeholders, content experts, and public member representatives to address issues of health equity and reexamine how race and ethnicity are addressed in our guidance. Moreover, ACOG will continue to review clinical recommendations and identify and address those that base clinical guidance, algorithms, and other practice patterns on race.
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