Бюллетень сибирской медицины (Aug 2019)

Risk factors and mathematical model of complicated pregnancy using integrative analysis

  • L. A. Agarkova,
  • I. Yu. Bukharina,
  • N. G. Belova,
  • A. L. Uliyanich,
  • E. M. Vershkova,
  • I. V. Tolmachev,
  • E. G. Murzina

DOI
https://doi.org/10.20538/1682-0363-2019-2-6-15
Journal volume & issue
Vol. 18, no. 2
pp. 6 – 15

Abstract

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Objective: To identify additional risk factors of complicated pregnancy and to develop a mathematical model for prognosing the course of gestation using integrative analysis.Materials and methods. We carried out a prospective parallel group study of 240 women with low perinatal risk in the first and second trimesters of pregnancy. To study the psycho-emotional state and personality characteristics of pregnant women, we used the SF-36 questionnaire, Osgood’s Semantic differential, G. Eysenck’s self-assessment personality test and the Big five questionnaire proposed by R. McCrae and P. Costa. To assess the impact of the environment on pregnancy, a questionnaire “Degree of satisfaction with the urban environment” composed by Yu.Kataeva was used.Results. We established additional criteria for predicting the course of gestation. In the first trimester they were restrictions of everyday functions due to painful manifestations and signs of early toxicosis, poor health, bad mood, high levels of anxiety, difficulty in being flexible in new life conditions and a tendency to react aggressively. In the second trimester they experienced painful conditions, mood swings, preferring seclusion to relationships and lack of satisfaction with the quality of the urban environment. During the interpretation of the study results we identified additional prognostic factors of the unfavorable course of pregnancy, which allow us to develop targeted programs for medical and psychological support during pregnancy. Conclusion. We investigated the interrelations between the most important factors affecting the normal course of pregnancy, childbirth and the condition of the newborn. This study will allow us to predict the course of pregnancy and elicit additional criteria to form groups with increased obstetric and perinatal risks. We also designed a mathematical model for prognosing the course of gestation that takes into account the identified additional criteria.

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