A Rubric to Center Equity in Obstetrics and Gynecology Research

Validation of a Vaginal Birth After Cesarean Delivery Prediction Model Without Race and Ethnicity in Individuals With Two Prior Cesarean Deliveries

Previous models for prediction of vaginal birth after cesarean (VBAC) relied on race and ethnicity, raising concern for bias. In response, the Maternal-Fetal Medicine Units Network (MFMU) created a new prediction model without race and ethnicity for individuals with one prior cesarean delivery. We performed a secondary analysis of the MFMU Cesarean Registry database to evaluate whether the MFMU VBAC prediction model without race and ethnicity could accurately predict VBAC for individuals with two prior cesarean deliveries. Overall, 353 individuals were included and 252 (71%) had VBAC. An area under the curve for the receiver operating curve of 0.74 (95% CI, 0.69-0.80) was reported for the predicted probabilities for VBAC, indicating that the model can be used for prediction of VBAC in this population.

Disparities in perinatal COVID-19 infection and vaccination

The COVID-19 pandemic exposed and exacerbated persistent health inequities in perinatal populations, resulting in disparities of maternal and fetal complications. In this narrative review, we present an adapted conceptual framework of perinatal social determinants of health in the setting of the COVID-19 pandemic and use this framework to contextualize the literature regarding disparities in COVID-19 vaccination and infection. We synthesize how elements of the structural context, individual socioeconomic position, and concrete intermediary determinants influence each other and perinatal COVID-19 vaccination and infection, arguing that systemic inequities at each level contribute to observed disparities in perinatal health outcomes. From there, we identify gaps in the literature, propose mechanisms for observed disparities, and conclude with a discussion of strategies to mitigate them.