Multi-Site Identification and Generalization of Clusters of Walking Behaviors in Individuals With Chronic Stroke and Neurotypical Controls.
Natalia Sánchez, Nicolas Schweighofer, Sara J Mulroy and 6 others
PMID 37975184WHAT IT FOUND
Walking patterns after stroke fall into four distinct, reproducible clusters, not just a single average profile.
Fast walkers show marked asymmetry, while slow walkers split into two groups with different force deficits. Identifying which cluster a patient belongs to allows for targeted rehabilitation strategies rather than generic gait training.
Key findings
01Four of the five identified walking clusters were stable and generalizable across multiple research sites, confirming distinct subgroups of walking behavior.
02Participants in the fast cluster exhibited significant asymmetry, with non-paretic propulsion 72% greater than paretic propulsion.
03Walking speed alone is insufficient to classify impairment subgroups, as clusters with overlapping speeds showed distinct differences in stance times and ground reaction forces.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTs
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What it does not show
The study used only ground reaction force data, which may miss joint-level kinematic or kinetic impairments that require more complex measurement. Control participants were only matched to one of the stroke samples (USC2021), potentially limiting the generalizability of the control comparison. Sample sizes across sites were unbalanced, which affected cluster stability in some cases. Data were collected on treadmills, which may alter walking patterns compared to overground walking. Some participants used handrails, which could influence gait mechanics. The analysis used average metrics, ignoring stride-to-stride variability. The study was cross-sectional, so it does not show how these clusters change over time or with intervention.
Declared interests
The authors declared no conflicts of interest. The work was supported by the National Institutes of Health (N.I.H., Extramural).
The easy way to misread this
Do not assume that the identified clusters represent distinct diagnostic categories that require entirely different treatments. The study shows that these clusters exist and are stable, but it did not test whether targeting these specific biomechanical deficits improves patient outcomes. The clinical relevance is currently based on the authors' hypotheses about potential interventions, not on tested efficacy.