The Disease Centered Multimorbidity Model at the Example of Type 2 Diabetes Mellitus

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Dmitry Meshkov
Alexey Lobanov
Larisa Danilova
Sergey Cherkasov
Alexander Shiroky
Anna Fedyaeva
Irina Moroz
Elena Makeeva

Abstract

Multimorbidity is a condition when few diseases (multimorbidity pattern) are diagnosed in same patient. According to the disease centered model the pattern is formed around one “marker” disease at the expense of other diseases which have non-random relationships with the “marker” disease and between each other. The totality and probabilistic connections between pairs of diseases determine the specifics of the pattern and indicate the possibilities for managing individual and population health as a result of interactions of all components of the the pattern. Algorithms have been developed assessing the degree of non-random connections between pairs of diseases in the pattern and establishing a hierarchical relationship between both “marker” and other diseases as well as between pairs of non-marker diseases. The calculation of non-random statistical relationships between pairs of diseases included in the T2DM (Type 2 Diabetes Mellitus) multimorbidity pattern proved the consistency of the data obtained with the current clinical description of T2DM pathogenesis and complications.

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How to Cite
Meshkov, D., Lobanov, A., Danilova, L., Cherkasov, S., Shiroky, A., Fedyaeva, A., Moroz, I., & Makeeva, E. (2023). The Disease Centered Multimorbidity Model at the Example of Type 2 Diabetes Mellitus. Advances in Systems Science and Applications, 23(1), 22-34. https://doi.org/10.25728/assa.2023.23.01.1376
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