Clinical evaluation of a first trimester algorithm predicting the risk of hypertensive disease of pregnancy.

BACKGROUND The aim of this study is to validate the Fetal Medicine Foundation (FMF) multiple logistic regression algorithm for prediction of risk of pre-eclampsia in an Australian population. This model, which predicts risk using the population rate of pre-eclampsia, a variety of demographic factors, mean maternal arterial blood pressure (MAP), uterine artery PI (UtA PI) and pregnancy-associated plasma protein A (PAPP-A), has been shown to predict early-onset pre-eclampsia (delivery prior to 34 weeks) in 95% of women at a 10% false-positive rate. METHODS All women who attended first trimester screening at the Royal Prince Alfred Hospital had their body mass index (BMI), MAP and UtA PI assessed in addition to factors traditionally used to assess aneuploidy (including PAPP-A MoM). After delivery, risks of early-onset (delivery prior to 34 weeks) pre-eclampsia, late pre-eclampsia and gestational hypertension were calculated using the FMF risk algorithm. RESULTS A total of 3099 women were screened and delivered locally. 3066 (98.9%) women had all data to perform pre-eclampsia screening available. This included 3014 (98.3%) women with a live birth, where risks of early pre-eclampsia were calculated. Twelve women were delivered before 34 weeks because of early pre-eclampsia with a prevalence of early pre-eclampsia of 1 in 256 pregnancies. Risks generated through the use of maternal history, MAP, UtA PI and PAPP-A detected 41.7 and 91.7% of early pre-eclampsia at a false-positive rate of 5 and 10%, respectively. CONCLUSIONS This study shows that the FMF early pre-eclampsia algorithm is effective in an Australian population.