Abstract
Background Multiple sclerosis (MS) is a chronic, progressive neurological disease characterized by demyelination and neurodegeneration, leading to physical disability, cognitive decline, and reduced quality of life. Despite advances in pharmacological therapy, rehabilitation remains a key component in patient management, yet individualized optimization strategies are still underdeveloped. Objective This study aimed to develop and validate an evidence-based algorithm for optimizing rehabilitation programs in MS patients based on clinical, neurological, and functional characteristics to improve quality of life. Methods A retrospective and prospective observational study was conducted on 110 anonymized MS patients with varying disease courses and disability levels. Clinical parameters included disease type, neurological deficits, Expanded Disability Status Scale (EDSS), and treatment regimens. Patients were stratified into rehabilitation profiles, and a structured algorithm was developed integrating motor, cognitive, and functional domains. Results The cohort demonstrated heterogeneity in disease presentation, with EDSS scores ranging from 1.0 to 8.5. The most common clinical manifestations included spastic tetraparesis, cerebellar ataxia, pelvic dysfunction, and cognitive impairment. Implementation of the algorithm resulted in improved functional outcomes, particularly in mobility, cognitive engagement, and independence in daily activities. Conclusion The proposed algorithm provides a structured, individualized approach to MS rehabilitation, aligning clinical characteristics with targeted interventions. This model supports improved quality of life and may serve as a framework for modern rehabilitation strategies. Bangladesh Journal of Medical Science Vol. 25 No. 03 July’26 Page: 777-783