Репозиторій Вінницького національного медичного університету імені М. І. Пирогова

Discriminant models of the likelihood and characteristics of multiple sclerosis progression in ukrainian men depending on body size parameters

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dc.contributor.author Gunas, M.М.
dc.contributor.author Moskovko, G.S.
dc.contributor.author Rutska, I.A.
dc.contributor.author Galunko, G.M.
dc.contributor.author Antoniuk, T.V.
dc.date.accessioned 2025-03-22T22:37:59Z
dc.date.available 2025-03-22T22:37:59Z
dc.date.issued 2024
dc.identifier.citation Discriminant models of the likelihood and characteristics of multiple sclerosis progression in ukrainian men depending on body size parameters / M.М. Gunas, G.S. Moskovko, I.A. Rutska [et al.] // Світ медицини та біології. – 2024. – № 4(90). – С. 34–38. uk_UA
dc.identifier.other DOI 10.26724/2079-8334-2024-4-90-34-38
dc.identifier.uri https://dspace.vnmu.edu.ua/123456789/8754
dc.description.abstract In young Ukrainian men, based on the characteristics of body size, reliable discriminant models were built, which allow with high probability (correctness of the classification matrix 100 % of cases, Wilks' Lambda statistics=0.051, p<0.0001) to attribute the studied subjects to “typical” for practically healthy people or the general group of patients with multiple sclerosis. Based on the characteristics of body size between multiple sclerosis men with mild (EDSS 1.5–2.0) and moderate (EDSS 3.5–4.5) disorders, a reliable interpretation of the obtained classification indicators is also possible with medium probability (correctness of the classification matrix 96.8 % of cases, Wilks' Lambda statistics=0.342, p<0.0001). uk_UA
dc.language.iso en uk_UA
dc.publisher Світ медицини та біології uk_UA
dc.subject nervous diseases uk_UA
dc.subject multiple sclerosis uk_UA
dc.subject anthropometric indicators uk_UA
dc.subject discriminant models uk_UA
dc.subject practically healthy and sick men uk_UA
dc.title Discriminant models of the likelihood and characteristics of multiple sclerosis progression in ukrainian men depending on body size parameters uk_UA
dc.type Article uk_UA


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