Identifying candidates for targeted gait rehabilitation after stroke: better prediction through biomechanics-informed characterization.
BACKGROUND
Walking speed has been used to predict the efficacy of gait training; however, poststroke motor impairments are heterogeneous and different biomechanical strategies may underlie the same walking speed. Identifying which individuals will respond best to a particular gait rehabilitation program using walking speed alone may thus be limited. The objective of this study was to determine if, beyond walking speed, participants' baseline ability to generate propulsive force from their paretic limbs (paretic propulsion) influences the improvements in walking speed resulting from a paretic propulsion-targeting gait intervention.


METHODS
Twenty seven participants >6 months poststroke underwent a 12-week locomotor training program designed to target deficits in paretic propulsion through the combination of fast walking with functional electrical stimulation to the paretic ankle musculature (FastFES). The relationship between participants' baseline usual walking speed (UWSbaseline), maximum walking speed (MWSbaseline), and paretic propulsion (propbaseline) versus improvements in usual walking speed (∆UWS) and maximum walking speed (∆MWS) were evaluated in moderated regression models.


RESULTS
UWSbaselineand MWSbaselinewere, respectively, poor predictors of ΔUWS (R2= 0.24) and ΔMWS (R2= 0.01). Paretic propulsion × walking speed interactions (UWSbaseline× propbaselineand MWSbaseline× propbaseline) were observed in each regression model (R2s = 0.61 and 0.49 for ∆UWS and ∆MWS, respectively), revealing that slower individuals with higher utilization of the paretic limb for forward propulsion responded best to FastFES training and were the most likely to achieve clinically important differences.


CONCLUSIONS
Characterizing participants based on both their walking speed and ability to generate paretic propulsion is a markedly better approach to predicting walking recovery following targeted gait rehabilitation than using walking speed alone.
Department of Physical Therapy and Athletic Training, College of Health and Rehabilitation Sciences: Sargent College, Boston University, Boston, MA, 02215, USA. louawad@bu.edu.|Wyss Institute For Biologically Inspired Engineering, Harvard University, Cambridge, MA, 02138, USA. louawad@bu.edu.
Louis N
LN
Awad
Department of Physical Therapy, University of Delaware, Newark, DE, 19713, USA.|Graduate Program in Biomechanics and Movement Science, University of Delaware, Newark, DE, 19713, USA.
Darcy S
DS
Reisman
Delaware Clinical and Translational Research ACCEL Program, Newark, DE, 19713, USA.|Biostatistics Core Facility, University of Delaware, Newark, DE, 19713, USA.
Ryan T
RT
Pohlig
Department of Physical Therapy, University of Delaware, Newark, DE, 19713, USA.|Graduate Program in Biomechanics and Movement Science, University of Delaware, Newark, DE, 19713, USA.|Delaware Clinical and Translational Research ACCEL Program, Newark, DE, 19713, USA.
Stuart A
SA
Binder-Macleod
Biomechanics; Efficacy; Electrical stimulation; FES; Gait; Locomotion; Physical Therapy; Prediction; Prognostic; Rehabilitation; Stroke; Walking
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