Introduction: The study aim was to predict the risk of climacteric syndrome (CS) developing in perimenopausal women with hypothyroidism (HT) according to the developed algorithm and mathematical model for timely preventive measures.
Material and methods: 146 perimenopausal women with autoimmune HT were enrolled in this study. Assessment of the severity of metabolic, neurovegetative and psychoemotional symptoms was graded according to the Blatt-Kupperman menopause index. All women were interviewed according to a specially designed questionnaire for predicting the development of severe CS. Multiple regression analysis was used to build a multifactorial mathematical model. Shapiro-Wilk and Kolmogorov-Smirnov criteria were used to assess the normality of the distribution of traits.
Results: Regression analysis was used to determine the most significant multicollinear risk factors for CS developing: pathology of the thyroid gland, smoking, alcohol consumption, adverse environmental conditions, low physical activity, history of stress and anxiety. The predicted value of the risk factor for severe CS with a high degree of probability was determined in 72 (49.32%) women, medium probability in 58 (39.73%) women, and low probability in 16 (10.95%) women.
Conclusions: The developed algorithm and mathematical model are informative and allow one to prevent CS and its complications. The decay of women's health starts many years before menopause and prevention of its consequences is an important task for the clinicians.
Keywords: climacteric syndrome; hypothyroidism; mathematical model; perimenopause; women.
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