Assessing fall risk in multiple sclerosis using patient-reported outcomes and wearable gait metrics.

Abstract

Background: Falls in people with multiple sclerosis (pwMS) lead to morbidity and expense.

Objective: Identify clinical metrics associated with falls.

Methods: Eighty-six pwMS completed fall surveys, timed 25-foot walk (T25FW), and motion analysis with Clario Opal devices. Logistic regression models were created.

Results: Median age was 54.5 years (range 21-73), 62% (53) were female. The cohort included 58% with relapsing (50) and 42% with progressive MS (36). Those who reported falling in the last year were older (median age 58 vs 52.5, p = .03) and had a higher Patient Determined Disease Step (PDDS) score (median 3 vs 1, p < .0001). Falls were associated with worse balance metrics including sway area (median 2.3 degrees² vs 1.2, p = .01), jerk (median 3.3 m²/s⁵ vs 1.6, p = .005), and slower T25FW (median 11.5 s vs 8; p < .0001). A multivariable regression model based on gait aid use and T25FW time >10.8 s (c = 0.80) was derived. Having both features portended a probability of falling of 0.97, while having neither, a probability of 0.26.

Conclusions: Falls in pwMS are more frequent in patients who are older, have higher PDDS, slower walking, and worse balance. Gait aid use and T25FW >10.8 s were strongly associated with falls in the past year.