Developing a new algorithm for first and second trimester preeclampsia screening in twin pregnancies

Abstract

OBJECTIVES: Construct a new preeclampsia predicting algorithm in twins. METHODS: Twins sampled at 10-13 and 16-20 gestational weeks and their marker values were log transformed into multiples of the gestation-specific medians (MoMs) for singletons and entered into a new logistic regression model with/without prior risk factors. RESULTS: The cohort included 9 PE (18 samples) and 96 unaffected cases (175 samples) twin pregnant women. The algorithm constructed of PlGF, PAPP-A, PP13, Doppler UTPI, and MAP with prior risk factors generated an area under the curve of 0.918, 75% detection rate for 10% false-positive rate. CONCLUSIONS: The algorithm effectively forecasted twin risk to develop PE.