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Publisher: Peytchinski Publishing Ltd.
ISSN: 1312-773X (Online)
Issue: 2022, vol. 28, issue4
Subject Area: Medicine
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DOI: 10.5272/jimab.2022284.4742
Published online: 19 December 2022
Original article
J of IMAB. 2022 Oct-Dec;28(4):4742-4748
MULTIVARIATE STATISTICAL ANALYSIS FOR ASSESSMENT OF THE RELATIONSHIPS BETWEEN BONE DENSITY, BIOGENIC ELEMENTS CONTENT, AND THE LEVEL OF OXIDATIVE STRESS IN OSTEOPOROTIC WOMEN
Radka Tomova1
, Svetla Asenova1, Rodina Nestorova2, Bisera Atanasova3, Liliya Atanasova4, Mariana Nikolova5, Miglena Slavova6,
1) Department of Chemistry and Biochemistry, Faculty of Pharmacy, Medical University of Pleven, Bulgaria.
2) Rheumatology centre "Saint Irina" Sofia, Bulgaria.
3) Department of Clinical Chemistry, Faculty of Medicine, Medical University of Sofia, Bulgaria.
4) Department of Physics and Biophysics, Faculty of Medicine, Medical University of Sofia, Bulgaria.
5) Department of Mental Health, Social work and Integrative Medicine, Middlesex University, London, United Kingdom.
6) IEES, Bulgarian Academy of Science, Sofia, Bulgaria.
ABSTRACT:
The aim of the present study is to reveal hidden relationships between bone density, biogenic elements content, and the level of oxidative stress of female patients with osteoporosis and osteopenia. Additionally, specific links between the patients are sought in order to interpret different similarity patterns of objects (patients) helping to a better understanding of the significance of the clinical variables for each identified similarity pattern.
Material and Methods: The input dataset consisting of 59 objects (patients) and 11 experimentally determined variables (clinical parameters) was subject to intelligent data analysis including cluster analysis (hierarchical and non-hierarchical mode) and factor analysis.
Results and Discussion: In the hierarchical dendrogram for clustering of 11 variables are formed 3 major clusters. We could assume that three factors (impact) are linked to the structure of the data set: descriptors responsible for osteoporosis diagnosis; descriptors (essential elements) related to osteoporosis status; descriptors related to the "overall health status impact”. The patients are clustered in 3 clusters corresponding to 3 different levels of health status (improving, worsening and intermediate) by K-means clustering. The specific descriptors are defined for each identified cluster.
Factor analysis shows that 3 latent factors explain nearly 70 % of the total variance of the system ˗ each of them with respective clinical meaning. A relationship is proven between T-score, diagnosis, and antioxidant activity by a 3D plot of factor loadings.
Conclusion: The multivariate statistical data interpretation for patients with osteoporosis problems reveals hidden relationships between specific similarity clusters among all patients or between the clinical parameters experimentally measured. It helps to better distinguish the variations between the specific groups and to determine the indicators for the variability. All this helps for more individual approachesto medical treatment.
Keywords: osteoporosis, calcium, oxidative stress, multivariate statistics,
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Please cite this article as: Tomova R, Asenova S, Nestorova R, Atanasova B, Atanasova L, Nikolova M, Slavova M. Multivariate statistical analysis for assessment of the relationships between bone density, biogenic elements content, and the level of oxidative stress in osteoporotic women. J of IMAB. 2022 Oct-Dec;28(4):4742-4748. DOI: 10.5272/jimab.2022284.4742
Correspondence to: Radka Tomova, Faculty of Pharmacy, Medical University of Pleven; 1, Kliment Ohridski Str., Pleven 5800, Bulgaria; E-mail: rtomova@mail.bg
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Received: 10 October 2022
Published online: 19 December 2022