Technologies for Prediction of Preeclampsia.

Unlabelled: was to develop technologies for predicting the development of preeclampsia (PE) based on biomedical and molecular-genetic predictors and the calculation of individual risks for this pregnancy complication.

Materials And Methods: The study involved 457 pregnant women. Of them, 147 women had chronic arterial hypertension (CAH); 109 pregnant women had CAH and secondary preeclampsia (PE); 201 patients had PE. The control group consisted of 105 pregnant women without hypertensive disorders or proteinuria. We performed a retrospective analysis of gestation course and labor outcomes, calculated risk factors using the Open Epi system and logistic regression method. Polymorphisms of genes controlling the vascular tone were identified in venous blood.

Results: There were identified risk factors for developing PE, including those in women with CAH: chronic pyelonephritis; baseline mean AP above 95 mm Hg and diastolic AP above 80 mm Hg; body mass index over 30; family history of arterial hypertension. The following were identified as additional predictors of PE: perinatal loss; premature labor; spontaneous miscarriage; PE and closed craniocerebral injuries in the past medical history; threatening miscarriage in the first trimester. Additional risk factors for PE in women with CAH were found: lack of regular antihypertensive therapy before pregnancy and in the first trimester; chronic gastritis; first pregnancy; tobacco smoking.Polymorphic variants of the (-786)C allele in the genotype in combination with the heterozygous genotype in the 1675G/A gene are associated with a high risk of CAH. The presence of alleles (-786)T/C and (-786)C, as well as a combination of alleles (-786)C and 894G/T, is associated with PE. The presence of alleles 704C, (-344)T, and 825T/T in the genotype, both individually and in combination, is a risk factor for the development of PE secondary to CAH. The data obtained made it possible to develop a method for predicting the onset of PE in women with CAH and a model for calculating the individual risk of PE, which formed the basis for a computer program.

Conclusion: Calculating the individual risks of PE using the technologies proposed by the authors allows identifying pregnant women belonging to the high-risk group on a timely basis, which ensures high-quality implementation of preventive measures, provides a personalized approach and the possibility to prove the need for additional examination of this category of patients.