A scientifically based system for predicting preeclampsia
Objective. To develop and substantiate a predictive system for the management of pregnant women with risk factors of preeclampsia.Sidorova I.S., Nikitina N.A.
Subjects and methods. A prospective cohort study was conducted in 150 pregnant women at risk for preeclampsia. Of them, there were 42 patients who subsequently developed preeclampsia (18 had early preeclampsia, 24 had late preeclampsia), 108 had no preeclampsia. A multivariate comparative analysis of anamnestic, clinical, and functional characteristics was carried out in pregnant women who subsequently developed preeclampsia. The time course of changes in the biomarkers of endothelial, placental dysfunction and impaired blood-brain barrier (BBB) permeability, such as TNF-α, VCAM, ICAM, VEGF, PIGF, sFlt-1, NSE, and GFAP, were traced.
Results. A model was developed and scientifically substantiated to determine the likelihood of preeclampsia in risk-group pregnant women, which encompassed the assessment of anamnestic characteristics, uterine artery blood flow, daily changes in daily blood pressures, and alterations in the biomarkers of endothelial, placental dysfunction, and impaired BBB permeability.
Conclusion. The pathophysiological changes preceding the clinical manifestation of preeclampsia permit prediction of its development just from the end of the first trimester of pregnancy.
Keywords
preeclampsia
prediction
TNF-α
VCAM
ICAM
VEGF
PIGF
sFlt-1
NSE and GFAP
endothelial dysfunction
chronic uteroplacental ischemia
Supplementary Materials
- Table 1. Relative risk of development of preeclampsia in patients at risk (logistic regression analysis)
- Table 2. Prognostic value of PI in the uterine arteries (PI a.u.) in determining the risk of pre-eclampsia,%
- Table 3. Logistic regression analysis of daily monitoring parameters of blood pressure in the prognosis of preeclampsia
- Table 4. Logistic regression analysis of biomarkers for predicting preeclampsia
- Table 5. The predictive value of the mathematical model in determining the risk of preeclampsia at the time of 10-14 weeks of pregnancy,%
- Table 6. The predictive value of the mathematical model in determining the risk of preeclampsia at the time of 18-24 weeks of pregnancy,%
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Received 16.12.2016
Accepted 23.12.2016
About the Authors
Sidorova Iraida Stepanovna, MD, Professor, RAS Corresponding Member, Honoured Scientist of the Russian Federation, I.M. Sechenov First Moscow State Medical University, Therapeutic Faculty, Department of Obstetrics and Gynaecology № 1. 119991, Russia, Moscow, Trubetskaya str. 8, bld. 2Nikitina Natalya Aleksandrovna, Candidate of Medical Sciences, Associate Professor of the Chair of Obstetrics and Gynaecology № 1, I.M. Sechenov First Moscow State Medical University, Therapeutic Faculty, Chair of Obstetrics and Gynaecology № 1. 119991, Russia, Moscow, Trubetskaya str. 8, bld. 2. E-mail: natnikitina@list.ru
For citations: Sidorova I.S., Nikitina N.A. A scientifically based system for predicting preeclampsia. Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2017; (3): 55-61. (in Russian)
http://dx.doi.org/10.18565/aig.2017.3.55-61
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