Objective: The aim of this study was to develop a multiparameter risk-based scoring system for first-trimester prediction of preeclampsia and to validate this scoring system in our patient population.
Study design: Secondary analysis of a prospective cohort of 1,200 patients presenting for first-trimester aneuploidy screening. Maternal serum pregnancy-associated plasma protein A (PAPP-A) levels were measured and bilateral uterine artery (UA) Doppler studies performed. Using the first half of the study population, a prediction model for preeclampsia was created. Test performance characteristics were used to determine the optimal score for predicting preeclampsia. This model was then validated in the second half of the population.
Results: Significant risk factors and their weighted scores derived from the prediction model were chronic hypertension (4), history of preeclampsia (3), pregestational diabetes (2), body mass index ≥ 30 kg/m(2) (2), bilateral UA notching (1), and PAPP-A MoM < 10 th percentile (1). The area under the curve (AUC) for the risk scoring system was 0.76 (95% confidence interval [CI], 0.69-0.83), and the optimal threshold for predicting preeclampsia was a total score of ≥ 6. This AUC did not differ significantly from the AUC observed in our validation cohort (AUC, 0.78 [95% CI, 0.69-0.86]; p = 0.75].
Conclusion: Our proposed risk factor scoring system demonstrates modest accuracy but excellent reproducibility for first-trimester prediction of preeclampsia.
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