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

利用患者自述结果和可穿戴步态指标评估多发性硬化症患者的跌倒风险

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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 degrees(2) vs 1.2, p = .01), jerk (median 3.3 m(2)/s(5) 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.

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