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.

KEYWORDS:

• PP13
• PlGF
• PAPP-A
• Doppler UTPI
• MAP

Acknowledgments

We thank Dr. Ruth Cohen, Hylabs for stimulating discussions, and Perkin Elmer Inc for their support, valuable comments and for testing the samples for PlGF and PAPP-A by Delfia Xpress.

Funding

This work was supported by The European Commission FP7 Project ASPRE (# 601852) (AT, LMS, HM). The funding body had no influence on the study design, methods, results or conclusions.

Additional information

Funding

This work was supported by The European Commission FP7 Project ASPRE (# 601852) (AT, LMS, HM). The funding body had no influence on the study design, methods, results or conclusions.