CG28
Motor and Cognitive Predictors of Fall Risk in Multiple Sclerosis

Thursday, June 2, 2016
Exhibit Hall
Lisa Glukhovsky, M.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Gabriel Hoffnung, MA , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Jason Botvinick, B.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Jeffrey G Portnoy, B.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Marnina B Stimmel, B.A. , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Roee Holtzer, PhD , Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY
Frederick W Foley, Ph.D. , School of Psychology, Yeshiva University, New York, NY



Background: Persons with multiple sclerosis (PwMS) carry a higher risk of falls; studies estimate at least 50% of PwMS may experience a fall over a 3- to 6-month period. As PwMS may manifest varying physical and neuropsychological symptoms with complex interactions, it is important to elucidate the relationship of these symptoms to fall risk.

Objectives:  The study aimed to examine motor and cognitive predictors of fall risk.

Methods: Data were collected from 30 participants at a large outpatient medical center in New Jersey. All participants signed informed consents and were diagnosed previously with MS. Participants were administered the 9-Hole Peg Test (9-HPT), Timed 25-Foot Walk (T25-FW), Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS), and Expanded Disability Status Scale (EDSS). Participants were also asked to provide demographic information and history of falls during the previous 2 months. Bivariate correlations were conducted to select covariate variables for logistic regressions. Binary logistic regressions were conducted to examine whether motor and cognitive symptoms each predict fall risk. Age, gender, disability level (EDSS), and verbal learning/memory (California Verbal Learning Test-Second Edition [CVLT-II] Total Immediate Recall) were entered into the first block of the regressions because prior studies have found these variables to be associated with mobility.

Results: Upper extremity function (9-HPT) and processing speed (SDMT Total) were found to correlate significantly with whether participants had fallen during the previous 2 months. After controlling for age, gender, disability level, verbal learning/memory, and walking speed, dominant upper extremity function significantly predicted number of falls (B = .204, = .029). In a second regression controlling for age, gender, disability level, and verbal learning/memory, processing speed significantly predicted number of falls (B = -1.285, = .035).

Conclusions: Reduced performance in dominant upper motor function and processing speed each predicted higher number of falls in PwMS. This research provides potentially valuable information about identification and reduction of fall risk for MS.