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Biological, biomechanical, and pain sensitivity effects of walk-run in people with self-reported knee osteoarthritis

Chow, T.; Uddin, N.; McManus, C.; Altai, Z.; Mei, Q.; Evans, D. W.; Waterworth, S.; Liew, B. X. W.

2025-10-17 orthopedics
10.1101/2025.10.16.25338143 medRxiv
Show abstract

ObjectivesParticipating in small volumes of high-impact exercises in older adults, like running, is beneficial to mitigate age-related musculoskeletal deterioration. The biological and pain effects of small volumes of running integrated within a walking program in people with knee osteoarthritis (OA) are unclear. This study aims to investigate the biological and pain responses to a walk-run program in people with self-reported knee OA. MethodsEight participants with self-reported knee OA completed a 25-minute walk-run program on a force-plate instrumented treadmill with optical motion capture. Peak knee moment and cumulative knee moment impulse were quantified during this exercise task. Pressure pain threshold (PPT) was measured at the knee and elbow before and immediately after the task. A cartilage stress marker, cartilage oligomeric matrix protein (COMP), was measured at baseline, immediately after exercise (Post) and 30 minutes after exercise (Post30). ResultsPPT did not significantly change at the knee ({Delta}7.28%, P = 0.700) or elbow ({Delta}-9.15%, P = 0.496). Percentage COMP significantly increased from baseline immediately post-exercise (Hedges g = 1.43), then returned to baseline concentration at Post30 (Hedges g = 0.07). No significant correlations were observed between COMP and knee joint moment indices. ConclusionsIncluding short periods of running within a primarily walking-based session does not lead to prolonged elevations in cartilage stress markers or altered pain sensitivity. Walk-run may be an inclusive method to enable people with knee OA to reap the benefits of high-impact exercise participation, without the risk of damaging cartilage or worsening pain.

Published in Frontiers in Sports and Active Living (predicted rank #3) · training set

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