Predicting the risk of severe menopausal syndrome in perimenopausal women with hypothyroidism

• Main Authors: N.V. Pasechko, O.O. Chukur, A.O. Bob, A.S. Sverstiuk
• Format: Article
• Language: English
• Published: Publishing House Zaslavsky 2021-05-01
• Series: Mìžnarodnij Endokrinologìčnij Žurnal
• Subjects: menopausal syndrome, women, hypothyroidism, prediction, mathematical model
• Online Access: http://iej.zaslavsky.com.ua/article/view/232651

Background. Every year the number of menopausal women increases. At this age, the prevalence of hypothyroidism (HT) reaches its peak. The problem of menopausal syndrome (MS) is relevant for patients with HT, concomitant endocrine disorders create a background for combination with dyshormonal factors. The purpose of the study: to propose an approach to predicting the risk of severe MS in perimenopausal women with HT according to the developed algorithm and mathematical model. Materials and methods. To predict the development of MS, 146 perimenopausal women with autoimmune HT were surveyed. ­Using multiple regression analysis, a prognostic model of the risk of severe MS was created. Results. Logistic regression analysis revealed the following most significant multicollinear risk factors for MS: smoking, alcohol consumption, adverse environmental conditions, physical activity, history of stress and anxiety, thyroid disease. A correlation matrix with calculation of regression coefficients and coefficient of determination was constructed, a mathematical model was created to determine the risk factor for the progression of MS. The predicted value of the risk factor for severe MS with a high degree of probability was determined in 72 (49.32 %) women, with an average probability — in 58 (39.73 %), and with a low probability — in 16 women (10.95 %) with HT. The correspondence of the predicted results with the theoretically expected ones in the high-risk group was recorded in 104.37 %, in the average-risk — in 94.73 %, and in the low-risk — in 89.65 % of cases. Conclusions. The developed algorithm and mathematical model for predicting severe MS on the background of HT are highly informative and allow determining in advance the group of women at high risk of severe MS for the timely implementation of appropriate preventive measures.