The invention develops a construction method of a novel
preeclampsia prediction model based on
insulin growth binding factor
binding protein 1 (IGFBP1) and
placental growth factor (PlGF) and related application of the novel
preeclampsia prediction model. Specifically, according to the method, IGFBP1 and / or PLGF of a pregnant woman,
clinical information and MAP data serve as input, whether the pregnant woman suffers from
preeclampsia or not serves as output, model construction is conducted through a
machine learning method, and a preeclampsia prediction model is obtained. As effective detection can be carried out only by adopting one or two
protein predictive markers without depending on the uterine
artery pulsation index, the cost is low, and on the whole, clinical popularization is more convenient, the medical expenditure is reduced, the mom and infant outcome is effectively improved, and the method has important significance on reducing the
mortality rate of pregnant and
lying-in women and infants.