Multifactorial Model of Predictors for the Development of Depressive Disorders Following Conversion of Clinically Isolated Syndrome to Definite Multiple Sclerosis: A Longitudinal Prospective Study
- Authors: Gubskaia K.V.1, Malygin Y.V.2, Khudyakov А.V.1, Odnorob E.N.1
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Affiliations:
- Ivanovo State Medical University
- Lomonosov Moscow State University
- Issue: Vol LVII, No 2 (2025)
- Pages: 124-131
- Section: Original study arcticles
- Submitted: 06.11.2024
- Accepted: 20.11.2024
- Published: 14.06.2025
- URL: https://journals.eco-vector.com/1027-4898/article/view/641670
- DOI: https://doi.org/10.17816/nb641670
- EDN: https://elibrary.ru/LOBUZS
- ID: 641670
Cite item
Abstract
BACKGROUND: The conversion rate of clinically isolated syndrome to multiple sclerosis may reach up to 50%. Irreversible brain damage may occur following a clinically isolated syndrome episode. However, it has not been considered as a risk factor for the development of mental disorders in patients with multiple sclerosis.
AIM: The work was aimed to develop a multifactorial model of predictors for the development of depressive disorders in patients with multiple sclerosis and a history of clinically isolated syndrome, considering sociodemographic, clinical and psychopathological, as well as clinical and functional characteristics.
METHODS: The following assessment tools were used: the Spielberger–Khanin Anxiety Scale, MFI-20 (Multidimensional Fatigue Inventory of 20 items), Beck Depression Inventory, visual analog scale for pain, PASAT (Paced Auditory Serial Addition Test), and EDSS (Expanded Disability Status Scale). Significant stressful life events, clinical course of multiple sclerosis, comorbid conditions, and magnetic resonance imaging findings were also considered. Depression was diagnosed based on the criteria of the 10th revision of the International Classification of Diseases. The analysis of variance and multiple linear regression equations were applied to develop multifactorial models of depression predictors. The study was conducted over a 10-year period.
RESULTS: The main group included 30 patients with multiple sclerosis and a history of clinically isolated syndrome who developed depression. The control group included 30 patients with multiple sclerosis and a history of clinically isolated syndrome without depression. The multifactorial model of predictors for depression demonstrated a high multiple correlation coefficient (r = 0.85). The following predictors had a pronounced impact on the development of depression: asthenia 60.6 ± 1.1 points on the MFI-20 scale, with an annual increase by 1.38 points (Beta = 0.733); an annual increase in the volume of existing brain lesions by 0.74% (Beta = 0.663); and anxiety measured using the Spielberger–Khanin scale (trait anxiety: 42.73 ± 0.43; state anxiety: 41.16 ± 0.41, with an annual increase in state anxiety by 1.43%; Beta = 0.622). Statistically significant but less influential predictors included female sex, secondary education, absence of family, history of major stressful life events, autoimmune diseases, predominant lesion localization in the frontal and temporal lobes of the right hemisphere, history of visual disturbances (optic neuritis), cognitive impairment (with an annual increase in the PASAT score of 2.47%), and elevated body mass index (with an annual increase by 1.67%).
CONCLUSION: A multifactorial model has been developed to support a personalized approach to providing specialized medical care for patients with clinically isolated syndrome converting to multiple sclerosis, based on the prediction of depressive disorder development.
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About the authors
Ksenya V. Gubskaia
Ivanovo State Medical University
Author for correspondence.
Email: dr.gubskaia@ya.ru
ORCID iD: 0009-0007-6952-2367
MD, Cand. Sci. (Med.), Assistant Professor at the Department of Psychiatry, Addiction Medicine and Psychotherapy, Institute of Postgraduate Education
Russian Federation, 8 Sheremetevsky ave, Ivanovo, 153012Yaroslav V. Malygin
Lomonosov Moscow State University
Email: malygin-y@yandex.ru
ORCID iD: 0000-0003-4633-6872
MD, Dr. Sci. (Med.), Associate Professor at the Department of Multidisciplinary Clinical Training, Faculty of Fundamental Medicine
Russian Federation, 1 Leninskiye gory, Moscow, 119991Алексей V. Khudyakov
Ivanovo State Medical University
Email: app237110@yandex.ru
ORCID iD: 0000-0002-1933-7936
MD, Dr. Sci. (Med.), Professor, Head of the Department of Psychiatry, Addiction Medicine and Psychotherapy, Institute of Postgraduate Education
Russian Federation, 8 Sheremetevsky ave, Ivanovo, 153012Evgeniy N. Odnorob
Ivanovo State Medical University
Email: k0ll3k70rw1n5@gmail.com
ORCID iD: 0009-0009-3189-1305
MD, Postgraduate Student at the Department of Psychiatry, Addiction Medicine and Psychotherapy, Institute of Postgraduate Education
Russian Federation, 8 Sheremetevsky ave, Ivanovo, 153012References
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