Assessing lower-limb prosthetic users with the amputee mobility predictor with prosthesis and timed up and go tests

BACKGROUND: Lower-limb amputation (LLA) significantly impacts mobility, independence, and quality of life. Reliable assessment tools are essential for evaluating functional capacity, guiding prosthetic prescription, and identifying individuals at risk of falls. The Amputee Mobility Predictor with prosthesis (AMPPro) and Timed Up and Go (TUG) test are commonly used performance-based measures, yet their complementary utility in clinical practice among LLA populations in Jordan remains underexplored. OBJECTIVE: To evaluate functional mobility among lower-limb prosthetic users using AMPPro and TUG, examine associations with demographic and clinical factors, and assess the predictive value of AMPPro for fall risk. STUDY DESIGN: Cross-sectional observational study. METHOD: Sixty-three adults with unilateral lower-limb amputation were assessed using AMPPro and TUG. Demographic and clinical data, including age, gender, amputation etiology, level, time since amputation, and time since first prosthetic fitting, were collected. Statistical analyses included Spearman correlations, non-parametric tests, and multivariable regression to examine associations and predictors of functional outcomes and fall risk. RESULTS: Participants were predominantly male (71.4%) with a mean age of 43.7 ± 14.5 years. Median AMPPro score was 43/47, and median TUG time was 14 s, with 54% at risk of falls. AMPPro and TUG were strongly inversely correlated (ρ = - 0.603, p < 0.001). Age and amputation cause significantly influenced functional outcomes, while time since amputation, time since first fitting, and amputation level did not. Each one-point increase in AMPPro reduced fall risk by 17% (OR = 0.83, p = 0.004). CONCLUSION: AMPPro and TUG provide complementary assessments of mobility in lower-limb prosthetic users. AMPPro effectively distinguishes functional levels and predicts fall risk, supporting its use alongside demographic and clinical data for individualized rehabilitation and fall-prevention strategies.