Thyroid and Bone Remodeling Markers in Premenopausal and Postmenopausal Women: A Multivariate Machine Learning Approach - Thakur, Rajesh Kumar; Dhakal, Rojiya; Joshi, Govardhan; Bista, Pabitra; Khadka, Anil; Khanal, Sudip; Acharya, Aashish; Gautam, Sujan; Lamichhane, Anit; Bhatt, Mahendra Prasad (Journal of Manmohan Memorial Institute of Health Sciences, 2026)
Introduction: Menopause induces significant hormonal shifts that may impact thyroid function and bone metabolism. This study aimed to compare thyroid profile (FT3, FT4, and TSH) and bone remodeling (serum calcium, phosphorus, and ALP) markers between premenopausal and postmenopausal women and to examine their predictive ability via multivariate and machine learning methods.Method: This cross-sectional study was performed among 178 women (89 premenopausal, 89 postmenopausal) attending Manmohan Memorial Teaching Hospital (MMTH), Kathmandu, Nepal. Serum levels of FT3, FT4, TSH, calcium, phosphorus, and ALP were estimated using standard methods. Statistical analyses were carried out by using Mann‒Whitney U tests, Spearman correlations, MANOVA, PCA, ANCOVA, and classification models such as logistic regression, LDA, SVM, and random forest.Result: Postmenopausal women had markedly higher TSH and ALP levels, wereas lower serum calcium and phosphorus levels. MANOVA revealed a significant multivariate effect of menopausal status (Wilks’λ= 0.6818, p