Israel Medical Association Journal

Background: Gait disturbances are common in patients undergoing hemodialysis and are associated with increased fall risk, mobility decline, and adverse health outcomes. Prior research suggests that hemodialysis may impact gait parameters such as speed, stride length, and variability; however, findings are inconsistent.

Objectives: To evaluate acute changes in gait metrics before and after hemodialysis using an artificial intelligence (AI) based video gait analysis system.

Methods: We initially enrolled 38 hemodialysis patients, two were excluded due to clothing interference with video analysis (27.8% female, 72.2% male). 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.

Conclusions: Dialysis does not acutely affect overall gait speed but significantly reduces stride length. 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.

Background: Diabetes mellitus is a multi-organ disorder affecting many types of connective tissues, including bone and cartilage. Certain skeletal changes are more prevalent in diabetic patients than in non-diabetic individuals. A possible association of diabetes mellitus and lumbar spinal stenosis has been raised.

Objectives: To compare the prevalence of diabetes mellitus in patients with spinal stenosis, degenerative disk disease or osteoporotic vertebral fractures.

Methods: A cross-sectional analysis was performed of 395 consecutive patients diagnosed with spinal stenosis, degenerative disk disease or osteoporotic vertebral fractures. All the patients were examined by one senior author in the outpatient orthopedic clinic of a large general hospital between June 2004 and January 2006 and diagnosed as having either lumbar spinal stenosis (n=225), degenerative disk disease (n=124) or osteoporotic vertebral fractures (n=46).

Results: The prevalence of diabetes mellitus in the three groups (spinal stenosis, osteoporotic fracture, degenerative disk disease) was 28%, 6.5% and 12.1%, respectively, revealing a significantly higher prevalence in the spinal stenosis group compared with the others (P = 0.001). The higher prevalence of diabetes in the stenotic patients was unrelated to the presence of degenerative spondylolisthesis.

Conclusions: There is an association between diabetes and lumbar spinal stenosis. Diabetes mellitus may be a predisposing factor for the development of lumbar spinal stenosis.