MATHEMATICAL MODEL FOR PREDICTING THE OCCURRENCE OF MODERATE PREECLAMPSIA IN WOMEN AT HIGH RISK OF DEVELOPING LATE GESTOSIS AGAINST THE BACKGROUND OF METABOLIC SYNDROME
DOI:
https://doi.org/10.11603/1811-2471.2021.v.i3.12530Keywords:
late gestosis, vitamin D, inhibin A, neural networksAbstract
In Ukraine, there is a tendency to an increase in the development of complications of pregnancy with late gestosis, therefore, a study using the method of mathematical modeling to predict the occurrence of moderate preeclampsia is advisable and necessary to simplify the verification of this pathology.
The aim – development of a mathematical model to determine the probability and percentage of predicting the occurrence of moderate preeclampsia in women at high risk of developing late gestosis against the background of metabolic syndrome.
Material and Methods. To date, in addition to accurate diagnosis and effective treatment of preeclampsia with obesity, the question has arisen of predicting the development of preeclampsia, using biochemical diagnostic markers. That is, with what probability may moderate preeclampsia occur in women at risk of developing late gestosis against the background of metabolic syndrome. To solve problems of such complexity, neural networks or "artificial intelligence" were used.
Results. It has been mathematically proven that in the presence of proteinuria, which meets the diagnostic criteria for mild preeclampsia, vitamin D deficiency and an increase in inhibin A, the probability of moderate preeclampsia is 89 %.
Conclusions. In patients over 35 years of age, the risk of moderate preeclampsia, given additional prognostic markers, in particular vitamin D and inhibin A, increases the likelihood of developing this complication of pregnancy against the background of metabolic syndrome.
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