The primary objective of this proof-of-concept study is to longitudinally track the development of post-stroke sensory reweighting (PSR), identify associated structural neuroanatomical correlates, and investigate their relationship to walking and fall outcomes.
Post-stroke imbalance and walking impairment is a function of diminished sensorimotor integration, motor, and postural control. It impacts over 75% of stroke survivors, and remain a rising cause of falls, fractures, and death in the United States. The associated fear of falling often leads to a downward spiral of health, characterized by reduced walking performance, caregiver dependency, social isolation, and the development of secondary post-stroke medical complications. Although spontaneous biological recovery and intensive clinical rehabilitation may improve balance and walking ability, the extent of recovery is often limited after the first 6-months of stroke (chronic phase). Furthermore, currently available clinical measures such as the Berg Balance Scale and Timed-Up-and-Go lack the specificity and granularity needed to foster the development of individualized and targeted neurorehabilitation interventions. In addition, non-invasive neurostimulation strategies lack specificity due to limited understanding of the most appropriate neuroanatomical targets for optimizing sensorimotor integration. Hence there is an urgent need to identify reliable physiologic and neuroanatomic correlates in the earlier stages of recovery (\<6 months), to enable timely and targeted rehabilitation interventions.
Study Type
OBSERVATIONAL
Enrollment
45
Successful completion of all four indices of the mCTSIB, without severe imbalance (i.e., near fall with safety harness and urgent knee to grab emergency handlebars) constitutes "PSR +", non-completing on any of the index is noted as "PSR -". Exploratorily, the average sway velocity index will be captured for each condition, to characterize sensory reweighting patterns.
The 10-meter walk test (10MWT) is the gold standard measure of post-stroke walking function that reflects overall mobility and health status. Method: Two 10MWT trials (using a stopwatch) are averaged and documented in meters/second. The functional ambulatory category (FAC) will be collected as supplement. Exploratorily: Participants will also perform the 10mWT (fast paced-FP) with two attempts. Both SS and FP will be performed over the Zeno Walkway Gait Analysis Mat, to capture supplementary spatiotemporal data.
University of Cincinnati College of Medicine
Cincinnati, Ohio, United States
RECRUITINGPosturography
MCTSIB
Time frame: 2, 4, and 6 months Post-Stroke
Walking Speed (10 meter Walk Test)
Self-Selected
Time frame: 2, 4, and 6 months Post-Stroke
Instrumented Timed UP and GO
7M ITUG
Time frame: 2, 4, and 6 months Post-Stroke
Fall Events
Record and characterization of Falls
Time frame: 2, 4, and 6 months Post-Stroke
Functional Ambulation Category
Determination of walking status
Time frame: 2, 4, and 6 months Post-Stroke
Walking Speed (10 meter Walk Test)
Fastest Speed
Time frame: Walking Speed (10 meter Walk Test)
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This sub-aim will use iTUG to determine the effects of BLT on dynamic balance. In contrast to the traditional TUG, inclusion of wearable triaxial accelerometers and gyroscopes-placement test increases the sensitivity (87%) and specificity (87%) for identifying individuals prone to falls. Two trials are averaged and documented in seconds. Secondary analysis will be performed on data obtained from the sensors to determine (stride length, stride velocity, cadence, peak arm swing velocity, and turning velocity, during the task), to correlate with the TUG time/speed. Time points: Same as Posturography and 10 MWT.
A robust fall incident journal elucidating the date, time, nature, and management of the fall event will be provided to all study participants for documentation. The study research coordinator will contact the patient/caregiver/facility to collect the data q2 weeks. A tally of the total number of fall events between visits will be recorded.
Structural neuroimaging biomarkers:. The fractional anisotropy map from the primary fiber population in each voxel will be resampled to MNI space (using the warp derived from structural preprocessing) and projected onto a template white matter skeleton using local maxima to further optimize registration accuracy. Small vessel disease parameters, including white matter hyperintensities using the Fazekas scale and number/site of microhemorrhages, will be recorded for exploratory analyses.