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Abstract Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifiable alterations that affect progression of knee pain and osteoarthritis (OA). To examine this, we applied machine learning (ML) approaches to gait data from wearable sensors in a large observational knee OA cohort, the Multicenter Osteoarthritis (MOST) study. Participants completed a 20-m walk test wearing sensors on their trunk and ankles. Parameters describing spatiotemporal features of gait and symmetry, variability and complexity were extracted. We used an ensemble ML technique (“super learning”) to identify gait variables in our cross-sectional data associated with the presence/absence of unilateral knee pain. We then used logistic regression to determine the association of selected gait variables with odds of mild knee pain. Of 2066 participants (mean age 63.6 [SD: 10.4] years, 56% female), 21.3% had mild unilateral pain while walking. Gait parameters selected in the ML process as influential included step regularity, sample entropy, gait speed, and amplitude dominant frequency, among others. In adjusted cross-sectional analyses, lower levels of step regularity (i.e., greater gait variability) and lower sample entropy(i.e., lower gait complexity) were associated with increased likelihood of unilateral mild pain while walking [aOR 0.80 (0.64–1.00) and aOR 0.79 (0.66–0.95), respectively].

Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifiable alterations that affect progression of knee pain and osteoarthritis (OA). To examine this, we applied machine learning (ML) approaches to gait data from wearable sensors in a large observational knee OA cohort, the Multicenter Osteoarthritis (MOST) study. Participants completed a 20-m walk test wearing sensors on their trunk and ankles. Parameters describing spatiotemporal features of gait and symmetry, variability and complexity were extracted. We used an ensemble ML technique ("super learning") to identify gait variables in our cross-sectional data associated with the presence/absence of unilateral knee pain. We then used logistic regression to determine the association of selected gait variables with odds of mild knee pain. Of 2066 participants (mean age 63.6 [SD: 10.4] years, 56% female), 21.3% had mild unilateral pain while walking. Gait parameters selected in the ML process as influential included step regularity, sample entropy, gait speed, and amplitude dominant frequency, among others. In adjusted cross-sectional analyses, lower levels of step regularity (i.e., greater gait variability) and lower sample entropy(i.e., lower gait complexity) were associated with increased likelihood of unilateral mild pain while walking [aOR 0.80 (0.64–1.00) and aOR 0.79 (0.66–0.95), respectively]. [ABSTRACT FROM AUTHOR]

Objective: Whether knee instability contributes to the increased risk of falls and fractures observed in persons with knee osteoarthritis (OA) has not been studied. We examined the association of knee buckling with the risk of falling and fall-related consequences in older adults with, or at high risk for, knee OA.Methods: At the 60-month visit of the Multicenter Osteoarthritis Study, men and women ages 55-84 years were asked about knee buckling in the past 3 months and whether they fell when a knee buckled. Falls and fall-related injuries in the past 12 months and balance confidence were assessed at 60 and 84 months. Multivariate logistic regression was used to assess the association of knee buckling with falls and their consequences.Results: A total of 1,842 subjects (59% women, mean ± SD age 66.9 ± 7.8 years, and body mass index 30.3 ± 5.7) were included. At 60 months 16.8% reported buckling and at 84 months 14.1% had recurrent (≥2) falls. Bucklers at 60 months had a 1.6- to 2.5-fold greater odds of recurrent falls, fear of falling, and poor balance confidence at 84 months. Those who fell when a knee buckled at baseline had a 4.5-fold, 2-fold, and 3-fold increased odds 2 years later of recurrent falls, significant fall injuries, and fall injuries that limited activity, respectively, and were 4 times more likely to have poor balance confidence.Conclusion: Interventions that reduce knee buckling may help prevent falls, fall-related injuries, and adverse psychological consequences of falls in persons with knee OA. [ABSTRACT FROM AUTHOR]