GAIT PARAMETERS (KINETIC AND KINEMATIC) AS POTENTIAL PREDICTOR OF FALL RISK IN PATIENTS WITH PARKINSON’S DISEASE

Background: Parkinson’s disease (PD) is characterized by progressive motor deficits, which may increase the risk of falls. Subtle alterations in gait biomechanics, particularly under dual-task conditions, could serve as early indicators of fall susceptibility. This study investigates kinetic and kinematic gait parameters as potential predictors of falls in PD. Objectives: • Primary: Identify objective kinetic and kinematic gait parameters that discriminate PD patients at higher fall risk. • Secondary: Characterize systematic gait changes in PD, including effects of dual-task cognitive load. Methods: A prospective observational study was conducted with 42 PD patients (age 30–75, idiopathic PD, independent walkers) and 14 healthy controls. Participants performed walking trials along a 10-meter linear path under single-task and dual-task (backward counting) conditions. Primary outcomes included knee flexion at heel strike (degrees) and antero-posterior ground reaction force (GRF) during initial foot contact (Net Braking Force, % of Body Weight). Secondary outcomes comprised spatiotemporal gait parameters and GRF subcomponents (Clawback, Braking, Propulsive forces). PD participants were prospectively monitored for falls over 12 months, enabling classification into PD Faller and Non-Faller groups. Mixed two-way ANOVA assessed effects of group (Faller vs Non-Faller) and body side (more vs less affected). Correlations between outcomes were evaluated via Pearson or Spearman coefficients, with subsequent MANOVA for multivariate interactions. Comparisons with healthy controls were conducted using repeated-measures MANOVA. Statistical significance was set at α = 0.05, with Bonferroni correction for post-hoc analyses. Results: • Primary outcomes: No significant differences were observed between Fallers and Non-Fallers, nor between more and less affected limbs, for either parameter. Multivariate analyses and regression models also failed to show significant predictive capability, reinforcing that absolute values of these parameters do not discriminate fall risk. Notably, Pearson correlation analysis revealed that in Fallers—but not in Non-Fallers—increased knee flexion at initial contact was associated with reduced braking effectiveness (r = 0.601; p = 0.005). • Secondary outcomes: walking speed and stride length were significantly affected by dual-tasking, with speed more prominently reduced. Between-group comparisons confirmed that these parameters effectively distinguish PD patients from HC, though no differences emerged within the PD cohort. In contrast, multivariate analysis of GRFs revealed no significant differences between groups, sides, or conditions. Conclusions: Fall risk may be better characterized by the relationships among gait variables rather than by their absolute values, reflecting broader patterns of locomotor control and coordination. This emphasizes the importance of multidimensional and relational approaches, integrating kinematics, kinetics, variability, and cognitive-motor interactions, to more accurately describe and predict fall risk in PD.