Objective: To validate the Weiniger model, a multivariable prediction model for placenta accreta spectrum (PAS). Design: Multicentre external validation study. Setting: Two tertiary care hospitals in the United States. Population: Cohort A included patients with risk factors (prior caesarean delivery, placenta praevia) and/or ultrasound features of PAS (variable risk) presenting to a tertiary care hospital. Cohort B patients were referred to a tertiary care hospital specifically for ultrasound features of PAS (higher risk). Methods: Weiniger model variables (prior caesarean deliveries, placenta praevia and ultrasound features of PAS) were retrospectively collected from both cohorts and predictive performance of the model was evaluated. Main Outcome Measures: Surgical and/or pathological diagnosis of PAS. Results: The model c-statistic in cohorts A and B was 0.728 (95% CI: 0.662, 0.794) and 0.866 (95% CI: 0.754, 0.977) signifying acceptable and excellent discrimination, respectively. Based on calibration curves, the model underestimated average PAS risk in both cohorts. In both cohorts, high risk was overestimated and low risk underestimated. Use of this model compared to a “treat all” strategy had greater net benefit at a threshold probability of > 0.25 in cohort A, but no net benefit in cohort B. Conclusions: This study provides multicentre external validation of the Weiniger model for PAS prediction, making it a useful triaging tool for management of this high-risk obstetric condition. Clinical usefulness of this model is influenced by the incidence of risk factors and PAS ultrasound features, with better performance in a variable-risk population at threshold probability >25%.

Objective: Little is known about the demographic and clinical factors associated with SARS-CoV-2 infection in pregnant women in the United States. The objective of this study was to evaluate the factors associated with SARS-CoV-2 infection in women admitted for labor and delivery, in the context of universal screening. Design: Prospective cohort study. Setting: Four Boston-area hospitals. Population: Convenience sample of all women admitted for delivery (n= 1,153). Methods: We reviewed the health records of all women admitted for delivery at the largest health system in Massachusetts between April 19-May 16, 2020. Factors evaluated for potential association with SARS-CoV-2 infection included age, BMI, race, co-morbidities, zip code, infection in a household member, number of children in the household, occupation, and insurance type. Main Outcome Measures: Risk of SARS-CoV-2 infection and associations between SARS-CoV-2 infection and clinical characteristics. Results: A total of 32 patients (2.8%, 95% confidence interval 1.9-3.9) tested positive for SARS-CoV-2 infection on admission for delivery; 24 (75.0%) of the patients who tested positive were asymptomatic. Factors associated with SARS-CoV-2 infection included: younger age, obesity, African-American or Hispanic race/ethnicity, residence in heavily affected communities, household member with known infection, essential worker occupation, and Medicaid insurance. 93.5% of patients testing positive for SARS-CoV-2 had one or more factors associated with disease acquisition. Conclusions: In this large sample of deliveries, SARS-CoV-2 infection was largely concentrated in patients with distinct demographic characteristics. Understanding factors associated with infection may inform public health efforts directed towards at risk populations and serve in counseling pregnant women.