A prediction model for placenta accreta spectrum: A multicentre external validation study.

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%.