TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/4
Browse
2 results
Search Results
Article The Relationship Between Trunk Control and Disability in Persons with Early Relapsing Multiple Sclerosis(2025-12-31) Uçar, Hasret; Ceylan, Nursena; Özvar, Güngör Beyza; Cinar, Bilge Piri; Acikgoz, Mustafa; Uçar, Arzucan Toksal; Ozakbas, SerkanThis study aims to investigate the relationship between physical disability and trunk control, balance, and gait parameters in persons with Relapsing Remitting Multiple Sclerosis (RRMS) who have a low Expanded Disability Status Scale (EDSS) score. Materials and Methods: Twenty-three RRMS patients with an age range of 18-50 years, EDSS score ≤ 3 were included in this study. The patients' level of disability (EDSS), trunk control) Trunk Impairment Scale - TIS), lower extremity functionality (Timed 25-Foot Walk Test - T25FW), upper extremity functionality (Nine Hole Peg Test- 9HPT), balance (Biodex Balance System) and gait (Zebris® FDM 2) were evaluated. Results: The mean EDSS score of 23 patients who participate in the study was 2,10±0,67. A moderate, negative correlation (r= -0.429) was found between EDSS and TIS-dynamic parameter, while a moderate, positive correlation (r= 0.608) was found with T25FW (p<0.05). A moderate, positive correlation was also found between EDSS and dominant and non-dominant 9HPT scores (respectively, r= 0.423, r= 0.498) (p<0.05). Conclusion: EDSS, is not sufficient alone in terms of functionality, especially in patients with low disability. In these early stage patients, trunk, upper extremity, gait and balance assessments should be included in routine assessments.Article Multipl Sklerozlu Bireylerde Yorgunluk Belirleyicilerinin Tanımlanması(2026-01-28) Özdoğar, Asiye Tuba; Alizada, Said; Şimşek, Yasemin; Ozakbas, Serkan; Yeşiloğlu, PervinObjective: This study aimed to define the predictors of fatigue in people with multiple sclerosis (MS, pwMS) by evaluating clinical and demographic factors, including disability level, physical performance, sleepiness, and depression. Material and Methods: A total of 747 pwMS were included in this cross-sectional study. Fatigue was assessed using the Modified Fatigue Impact Scale (MFIS), and multiple linear regression analyses were performed to determine the predictors of fatigue based on total MFIS and its subdomains (physical, cognitive, psychosocial). Independent variables included age, disease duration, number of relapses, number of disease- modifying therapies (DMTs), Expanded Disability Status Scale (EDSS) score, Timed 25-Foot Walk (T25FW), Nine-Hole Peg Test (N-HPT), Epworth Sleepiness Scale (ESS), and Beck Depression Inventory (BDI). Results: Higher fatigue scores were significantly associated with increased EDSS scores (β=0.191, p<0.001), greater sleepiness (ESS, β=0.188, p<0.001), and higher depression scores (BDI, β=0.556, p<0.001). Slower walking performance (T25FW) was also a significant but weaker predictor (β=-0.09, p=0.02). Similar patterns were observed across MFIS subdomains. Number of DMTs, disease duration, number of relapses, and N-HPT performance were not significant predictors. Conclusion: Disability level, sleepiness, and depression were the most prominent predictors of fatigue in pwMS. These findings emphasize the importance of integrating physical, psychological, and sleep-related assessments into comprehensive fatigue management strategies for pwMS.