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

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.