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Using the Instrumented Sway System (ISway) to Identify and Compare Balance Domain Deficits in People With Multiple
Patrick G Monaghan1, Andrew S Monaghan2, Andrew Hooyman3
1School of Kinesiology, Auburn University, Auburn, AL.
Objective:
To develop a multiple sclerosis (MS)-specific model of balance and examine differences between (1) MS and neurotypical controls and (2) people with MS (PwMS) with (MS-F) and without a fall history (MS-NF).
Design And Setting:
A cross-sectional study was conducted at the Gait and Balance Laboratory at the University of Kansas Medical Center. Balance was measured from the instrumented sway system (ISway) assessment.
Participants:
In total, 118 people with relapsing-remitting MS (MS-F=39; MS-NF=79) and 46 age-matched neurotypical controls.
Intervention:
Not applicable.
Outcome Measures:
A total of 22 sway measures obtained from the ISway were entered into an exploratory factor analysis to identify underlying balance domains. The model-derived balance domains were compared between (1) PwMS and age-matched, neurotypical controls and (2) MS-F and MS-NF.
Results:
Three distinct balance domains were identified: (1) sway amplitude and velocity, (2) sway frequency and jerk mediolateral, and (3) sway frequency and jerk anteroposterior, explaining 81.66% of balance variance. PwMS exhibited worse performance (ie, greater amplitude and velocity of sway) in the sway velocity and amplitude domain compared to age-matched neurotypical controls (P=.003). MS-F also exhibited worse performance in the sway velocity and amplitude domain compared to MS-NF (P=.046). The anteroposterior and mediolateral sway frequency and jerk domains were not different between PwMS and neurotypical controls nor between MS-F and MS-NF.
Conclusions:
This study identified a 3-factor, MS-specific balance model, demonstrating that PwMS, particularly those with a fall history, exhibit disproportionate impairments in sway amplitude and velocity. Identifying postural stability outcomes and domains that are altered in PwMS and clinically relevant (eg, related to falls) would help isolate potential treatment targets.
