Artificial intelligence in obstetrics for predicting acute cerebrovascular disorders

• Emmanuella A. Bayanduryan
• Margarita D. Andreeva

Abstract

The incidence of acute cerebrovascular accidents (ACVA) remains high among pregnant women and is 3–13 times higher than the frequency in the population. Pregnancy is considered today as a kind of screening test for thrombotic pathology, as pregnancy in the norm is accompanied by hypercoagulability. Somatic pathologies (obesity, chronic arterial hypertension, cardiac rhythm disorders, etc.), as well as a range of obstetric complications (severe preeclampsia, HELLP-syndrome, amniotic fluid embolism, etc.), only increase the risks of developing acute cerebrovascular disorders during gestation. All these data indicate the need to study the risk factors for acute cerebrovascular disorders during pregnancy, in the postpartum period, and in the intergenic interval, as well as to address the issue of preventive therapy.

The aim of the study was to investigate risk factors for development of acute cerebrovascular accidents during pregnancy, postpartum period and in the intergenetic interval to build a prognostic model aimed at preventing vascular disorders.

Material and methods. 80 birth histories were prospectively studied, from which two groups were formed: 1^st group (n=50), consisting of pregnant women who suffered episodes of acute cerebrovascular accident during pregnancy or in the postpartum period, as well as with episodes of acute cerebrovascular accident in intergenetic interval, and 2^nd group (n=30), which consisted of birth histories of apparently healthy patients. Statistical analysis was carried out using the Statistica 13.3 program (USA, Tibco).

Results. Analysis of clinical and laboratory data in pregnant women who suffered episodes of acute cerebrovascular accident during pregnancy, after childbirth and in the intergenetic interval (1^st group) in comparison with apparently healthy pregnant women (2^nd group) allowed us to develop a prognostic model for identifying a group at risk for developing the pathology. The implementation of this model in clinical practice allowed, through additional clinical and laboratory research and risk calculations for acute cerebrovascular disorders, to conduct preventive therapy for 20 patients with a high risk of acute cerebrovascular accident, as well as for patients with a history of acute cerebrovascular accident who were preparing for pregnancy.

Conclusion. The absence of episodes of circulatory disorders in 20 patients with a high risk of developing acute cerebrovascular accidents confirms high predictive properties of the developed model.

Keywords: pregnancy; acute cerebrovascular accident; prognostic modelAbstract

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