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First trimester screening for early and late preeclampsia based on maternal characteristics, biophysical parameters, and angiogenic factors
Author(s) -
Crovetto Francesca,
Figueras Francesc,
Triunfo Stefania,
Crispi Fatima,
RodriguezSureda Victor,
Dominguez Carmen,
Llurba Elisa,
Gratacós Eduard
Publication year - 2015
Publication title -
prenatal diagnosis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.956
H-Index - 97
eISSN - 1097-0223
pISSN - 0197-3851
DOI - 10.1002/pd.4519
Subject(s) - preeclampsia , medicine , soluble fms like tyrosine kinase 1 , placental growth factor , obstetrics , logistic regression , gestation , pregnancy , uterine artery , prospective cohort study , gestational age , nested case control study , population , gynecology , cohort , biology , genetics , environmental health
Objective The aim of this article is to develop the best first‐trimester screening model for preeclampsia (PE) based on maternal characteristics, biophysical parameters, and angiogenic factors in a low‐risk population. Methods A prospective cohort of 9462 pregnancies undergoing first‐trimester screening is used. Logistic regression predictive models were developed for early and late PE (cut‐off of 34 weeks' gestation at delivery). Data included the a priori risk (maternal characteristics), mean arterial pressure (MAP), and uterine artery (UtA) Doppler (11–13 weeks) in all cases. Plasma levels (8–11 weeks) of human chorionic gonadotrophin, pregnancy‐associated plasma protein A, placental growth factor (PlGF), and soluble Fms‐like tyrosine kinase‐1 (sFlt‐1) were analyzed using a nested case–control study design. Results The best model for early PE ( n = 57, 0.6%) included a priori risk, MAP, UtA Doppler, PlGF, and sFlt‐1 achieving detection rates of 87.7% and 91.2% for 5% and 10% false‐positive rates, respectively (AUC: 0.98 [95% CI: 0.97–0.99]). For late PE ( n = 246, 2.6%), the best model included the a priori risk, MAP, UtA Doppler, PlGF, and sFlt‐1 achieving detection rates of 68.3% and 76.4% at 5% and 10% of false‐positive rates, respectively (AUC: 0.87 [95% CI: 0.84–0.90]). Conclusion Preeclampsia can be predicted with high accuracy in general obstetric populations with a low risk for PE, by combined algorithms. Angiogenic factors substantially improved the prediction. © 2014 John Wiley & Sons, Ltd.