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Fall Risk is Related to Cognitive Functioning in Ambulatory Multiple Sclerosis Patients

Overview
Journal Neurol Sci
Specialty Neurology
Date 2023 Mar 30
PMID 36997775
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Abstract

Background And Aims: Patients with multiple sclerosis (PwMS) may suffer severely from falling and gait disturbance. Cognitive dysfunction, a common condition in MS patients, may also increase falling rates, regardless of physical disability. We planned this study to determine the fall rate and risk factors in MS patients, follow patients for falls, and reveal the relationship between falls and cognitive dysfunction.

Methods: The study was conducted on 124 patients who have RRMS diagnoses. Patients' gait speed, simultaneous gait speed during other tasks, functions of the upper extremity, balance rating, and fear of falling were evaluated with dual-task Timed-Up-and-Go-3 versions (TUG, TUG-C, TUG-M), Timed 25 Foot Walk (T25WFT), Nine Hole Peg Test (9HPT), Berg Balance Scale (BBS) and Falls Efficacy Scale-International (FES-I) tests. Cognitive functions, fatigue levels, and quality of life were measured with the Symbol Digit Modalities Test (SDMT), Fatigue Severity Scale (FSS), and Multiple Sclerosis Quality of Life (MSQoL) test. Two groups were formed as "fallers" and "non-faller patients". We monitored the patients in six months period.

Results: Forty-six patients fell at least once in the last one year before the study began. Fallers were older, less educated, had lower SDMT scores and higher disability scores. Non-faller patients scored lower in FES-I, TUG, and FSS tests. SDMT scores showed statistically significant, linear, positive, and moderate correlation with BBS and 9HPT scores (r = 0.307, p = 0.038, and r = 0.320, p = 0.030, respectively).

Conclusion: We determined that advanced age, lower education level, and cognitive dysfunction adversely affect gait speed and balance. Among the fallers, those with lower SDMT and MoCA scores had higher falling rates. We determined that EDSS and BBS scores are predictive factors for falls in patients with MS. In conclusion, patients with cognitive impairment should be closely monitored for the risk of falling. Consideration of falls during follow-up examinations might be predictive of cognitive deterioration in patients with MS.

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References
1.
Lublin F, Reingold S, Cohen J, Cutter G, Soelberg Sorensen P, Thompson A . Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. 2014; 83(3):278-86. PMC: 4117366. DOI: 10.1212/WNL.0000000000000560. View

2.
Deloire M, Ruet A, Hamel D, Bonnet M, Dousset V, Brochet B . MRI predictors of cognitive outcome in early multiple sclerosis. Neurology. 2011; 76(13):1161-7. PMC: 3312081. DOI: 10.1212/WNL.0b013e318212a8be. View

3.
Gunn H, Newell P, Haas B, Marsden J, Freeman J . Identification of risk factors for falls in multiple sclerosis: a systematic review and meta-analysis. Phys Ther. 2012; 93(4):504-13. DOI: 10.2522/ptj.20120231. View

4.
Prosperini L, Castelli L, De Luca F, Fabiano F, Ferrante I, De Giglio L . Task-dependent deterioration of balance underpinning cognitive-postural interference in MS. Neurology. 2016; 87(11):1085-92. DOI: 10.1212/WNL.0000000000003090. View

5.
DOrio V, Foley F, Armentano F, Picone M, Kim S, Holtzer R . Cognitive and motor functioning in patients with multiple sclerosis: neuropsychological predictors of walking speed and falls. J Neurol Sci. 2012; 316(1-2):42-6. DOI: 10.1016/j.jns.2012.02.003. View