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甲状腺功能减退围绝经期女性更年期综合征发生情况的预测

Prediction of climacteric syndrome development in perimenopausal women with hypothyroidism.

作者信息

Chukur Oksana, Pasyechko Nadiya, Bob Anzhela, Sverstiuk Andrii

机构信息

Horbachevsky Ternopil National University, Ternopil, Ukraine.

出版信息

Prz Menopauzalny. 2022 Dec;21(4):236-241. doi: 10.5114/pm.2022.123522. Epub 2022 Dec 30.

Abstract

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.

摘要

引言

本研究旨在根据所开发的算法和数学模型预测围绝经期甲状腺功能减退症(HT)女性患更年期综合征(CS)的风险,以便及时采取预防措施。

材料与方法

本研究纳入了146例患有自身免疫性HT的围绝经期女性。根据布拉特-库珀曼绝经指数对代谢、神经植物神经和心理情绪症状的严重程度进行评估。所有女性均根据一份专门设计的用于预测严重CS发生的问卷进行访谈。采用多元回归分析建立多因素数学模型。使用夏皮罗-威尔克和柯尔莫哥洛夫-斯米尔诺夫准则评估性状分布的正态性。

结果

采用回归分析确定CS发生的最显著多共线性风险因素:甲状腺疾病、吸烟、饮酒、不良环境条件、低体力活动、应激和焦虑史。72例(49.32%)女性发生严重CS的风险因素预测值为高概率,58例(39.73%)女性为中概率,16例(10.95%)女性为低概率。

结论

所开发的算法和数学模型具有参考价值,可用于预防CS及其并发症。女性健康的衰退在绝经前很多年就开始了,预防其后果是临床医生的一项重要任务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8112/9871991/e7212005787c/MR-21-49553-g001.jpg

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