Abstract: FR-PO0414
Immediate Impact of Hemodialysis on Gait Metrics
Session Information
- Dialysis: Measuring and Managing Symptoms and Syndromes
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Dialysis
- 801 Dialysis: Hemodialysis and Frequent Dialysis
Authors
- Cernes, Relu, Edith Wolfson Medical Center, Holon, Israel
- Hershkovitch, Oded, Edith Wolfson Medical Center, Holon, Israel
- Tsehovsky, Tatyana, Edith Wolfson Medical Center, Holon, Israel
- Feldman, Leonid, Edith Wolfson Medical Center, Holon, Israel
- Lotan, Raphael, Edith Wolfson Medical Center, Holon, Israel
Background
Gait disturbances are common in patients undergoing hemodialysis (HD) and are associated with increased fall risk, mobility decline, and adverse health outcomes. Prior research suggests that HD may impact gait parameters such as speed, stride length, and variability, but findings are inconsistent. This study evaluated acute changes in gait metrics before and after HD using an artificial intelligence (AI) based video gait analysis system.
Methods
Thirty-eight hemodialysis patients were initially enrolled, with two excluded due to clothing interference with video analysis (27.8% male, 72.2% female). AI-driven gait analysis was performed immediately before and after dialysis. The system extracted spatiotemporal gait and joint range of motion. Statistical analyses included the Shapiro-Wilk test for normality, Wilcoxon signed-rank tests for non-normally distributed data, and paired t-tests for normally distributed data (p < 0.05).
Results
Gait speed (0.59 m/sec pre-dialysis) remained unchanged post-dialysis (p = 0.876), as did cycle length and time. However, step length significantly decreased post-dialysis (p = 0.001), suggesting a more conservative gait pattern. Knee flexion and extension increased slightly but did not reach statistical significance.
Conclusion
This study demonstrates that dialysis does not acutely affect overall gait speed but significantly reduces stride length. These findings suggest that post-dialysis fatigue or hemodynamic shifts may alter walking patterns, highlighting the need for fall prevention strategies and physical rehabilitation interventions in dialysis care. AI-based gait analysis may provide a practical tool for monitoring mobility changes in hemodialysis patients.