Background: There exists a dearth of evidence on rehabilitation factors that influence prosthetic mobility in people with lower limb amputation (LLA). Examining variables that contribute to prosthetic mobility can inform rehabilitation interventions, providing guidance in developing more comprehensive care for these individuals. Objective: To determine the influence of modifiable and non-modifiable variables related to LLA and their impact on prosthetic mobility, using the International Classification of Functioning, Disability and Health (ICF) model. Secondarily, to determine if personal factors and self-reported balance and mobility are predictive of Component timed-up-and-go (cTUG) performance. Design: Cross-sectional study of a convenience sample. Setting: National conference. Participants: People (N=68) with non-vascular causes of unilateral LLA. Methods: Assessment of anthropometrics, mobility, bilateral hip extensor strength, hip range of motion, single limb balance, and self report measures. Lasso linear regression and extreme gradient boosting analyses were used to determine influence of variables on prosthetic mobility. Main Outcome Measure: Timed performance of the cTUG. Results: The following five variables were found to influence basic prosthetic mobility (P ≤.05) in people with transtibial amputation: hip extensor strength, hip range of motion, single limb balance, waist circumference, and age. In the transfemoral cohort, number of comorbidities and waist circumference primarily influenced prosthetic mobility. Additionally, 66% of the variance in cTUG total time for the entire sample could be explained by simply regressing on level of amputation, number of comorbidities, age and Activities-specific Balance Confidence scale score, all variables easily collected in a waiting room. Conclusion: Variables that are modifiable with physical therapy intervention including hip extensor strength, hip range of motion, single limb balance, and waist circumference significantly influenced basic prosthetic mobility. These variables can be affected by targeted rehabilitation interventions and lifestyle changes. Level of Evidence: II.
|Number of pages||10|
|Journal||PM and R|
|State||Published - Feb 1 2020|
Bibliographical noteFunding Information:
for this research was provided by the United States Department of Defense (DOD)-Veterans Affairs (VA) Joint Incentive Fund (JIF) Project Titled “Mobile Device Outcomes Based Rehabilitation Program” (#P14169).
© 2019 American Academy of Physical Medicine and Rehabilitation
ASJC Scopus subject areas
- Physical Therapy, Sports Therapy and Rehabilitation
- Clinical Neurology