Risk factors and mathematical model of complicated pregnancy using integrative analysis

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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