Algorithm for physical rehabilitation of patients with multiple sclerosis: practical experience

Author:

Kuzminova Tatyana A.ORCID,Fedorenko Yana V.ORCID,Ivanova Galina E.ORCID,Ryabov Sergey A.ORCID,Boyko Olga V.ORCID,Boyko Alexey N.ORCID

Abstract

BACKGROUND: Multiple sclerosis is a pressing problem of modern society and healtcare. The high risk of disability of the able-bodied population, together with the observed trend of increase in morbidity and decrease in the age of onset of the disease, create a number of economic and social difficulties. It is well known that current medical treatment of multiple sclerosis is most effective in reducing the frequency of exacerbations and disability progression, but does not affect the already established residual manifestations, indicators of disability progression objectified by magnetic resonance imaging data. AIM: Evaluation of the effectiveness of using the algorithm for choosing a method of physical rehabilitation, according to the selected models of patients with multiple sclerosis. MATERIALS AND METHODS: The medical histories of patients aged from 31 to 58.8 (average age 48.9±8.6) years who were in hospital treatment were analyzed (n=504; men — 34%, women — 66%), of which 56% had no disability, 11% had disability group I, 25% had disability group II, and 8% had disability group III. RESULTS: An algorithm for working with patients in this category was developed from the perspective of functioning in the categories of the International Classification of Functioning, Disability and Health, and Assessment of Impairments, which is a huge part of the medical rehabilitation protocol for patients with multiple sclerosis. CONCLUSION: The proposed models of patients, including pronounced disorders, make it possible to systematize and standardize the process of rehabilitation measures, improve the quality of provided medical services and provide the population with qualified rehabilitation care.

Publisher

Federal Research and Clinical Center for Resuscitation and Rehabilitation

Subject

General Medicine

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