Related Experiment Video
Updated: Feb 14, 2026

Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
Differences in Physical Performance Measures Among Patients With Unilateral Lower-Limb Amputations Classified as
Jaclyn Megan Sions1, Emma Haldane Beisheim1, Tara Jo Manal1
1Department of Physical Therapy, University of Delaware, Newark, DE.
Objective:
To determine whether differences in physical function, assessed via self-report questionnaires and physical performance tests, exist between individuals with lower-limb loss using a prosthetic device classified as a K3 versus a K4 functional level.
Design:
Cross-sectional study.
Setting:
A university physical therapy amputee clinic.
Participants:
Participants (N=55) were included if they (1) were aged ≥18 years with a unilateral transfemoral or transtibial amputation; (2) were classified as K3 or K4 functional level; (3) completed all relevant outcome measures; and (4) were currently using a prosthesis.
Interventions:
Not applicable.
Main Outcome Measures:
Locomotor Capabilities Index (LCI), Prosthetic Evaluation Questionnaire-Mobility Section (PEQ-MS), Timed Up and Go (TUG), 10-Meter Walk Test (10MWT), Amputee Mobility Predictor (AMPPRO), and 6-Minute Walk Test (6MWT). K level was determined by group consensus based on a standardized clinical evaluation.
Results:
After controlling for covariates, patients classified as K3 had slower TUG times (P=.002) and self-selected and fast gait speeds (P<.001), lower AMPPRO scores (P<.001), and walked shorter distances during the 6MWT (P=.003) when compared with patients classified as K4. No significant between-group differences for the LCI or PEQ-MS were found.
Conclusions:
Clinicians involved in prosthetic prescription may consider including the TUG, 10MWT, AMPPRO, and 6MWT during their clinical evaluations to help differentiate between individuals of higher functional mobility. The LCI and PEQ-MS may be less useful in classifying individuals as K3 versus K4 because of a ceiling effect.
More Related Videos
08:11Assessing Forelimb Function after Unilateral Cervical SCI using Novel Tasks: Limb Step-alternation, Postural Instability and Pasta Handling
Published on: September 16, 2013
05:59Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Related Concept Videos
Classifying Matter by Composition
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures.
A pure substance is a form of matter that has a constant composition throughout with uniform properties. For example, any sample of sucrose has the same composition and same physical properties, such as melting point, color, and sweetness, regardless of the source from which it is isolated.
A mixture is composed of two or...
Ratio Level of Measurement
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
Ordinal Level of Measurement
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
Interval Level of Measurement
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
Nominal Level of Measurement
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
Classifying Matter by State