PREDICTION OF COGNITIVE DYSFUNCTION IN PATIENTS WITH MULTIPLE SCLEROSIS
DOI:
https://doi.org/10.32689/2663-0672-2024-4-1Keywords:
multiple sclerosis, cognitive dysfunction, prognostic factorsAbstract
Multiple sclerosis (MS) is a chronic autoimmune disease characterized by myelin destruction, neurodegenerative changes, and cognitive impairments. One of the most common and insufficiently studied manifestations of MS is cognitive dysfunction (CD), which significantly affects patients' quality of life. Objective. To identify and analyze factors influencing the development of cognitive dysfunction in patients with multiple sclerosis. Methodology. Between 2021 and 2023, a study was conducted in the neurology department of the Dnipropetrovsk Regional Hospital named after I.I. Mechnikov. A total of 93 patients with a confirmed diagnosis of MS were included. Neuropsychological assessment methods (MoCA, MMSE, Schulte tests, Rybakov tests) and morphological indicators (brain atrophy indices) were used. Data were processed using non-parametric statistics. Logistic regression and ROC analysis were applied to predict CD. Scientific novelty. It was found that the key predictors of CD include age, disease duration, neurological deficit level (EDSS), and the subcortical atrophy index (BCR). The application of multiple logistic regression models improves the accuracy of CD prediction (AUC = 0.97). High efficiency of cognitive tests and instrumental diagnostic methods was established. Conclusions. Comprehensive assessment of cognitive functions, including testing and neuroimaging, allows for the early detection of CD. This facilitates the development of personalized rehabilitation programs and improves the quality of life for patients with MS. The use of brain atrophy indices and EDSS is recommended for regular monitoring of cognitive status.
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