Title:
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Predicting walking following lower limb amputation
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Lower limb amputation is a common clinical problem with around 7,000 leg
amputations occurring in the UK per year. This commonly results in
impaired mobility, which may also influence an individual's quality of life
and independence. However, it is difficult to predict walking ability with a
prosthesis accurately.
The objective of this thesis is to establish whether simple clinical tests can
be used to predict walking outcome following lower limb amputation .
A systematic literature review, performed to establish current knowledge
regarding predictors of walking following lower limb amputation, found
inconsistent results and variability in methodology making comparison
difficult.
Data were collected to ascertain the current clinical assessment practice
and mobility outcome for lower limb amputees in Leeds. This indicated that
only around one third of patients achieve independent walking with a
prosthesis.
A qualitative interview study was completed with clinicians experienced in
amputee rehabilitation to explore in more depth the decision making
processes that are used to determine whether a patient is supplied with a
prosthesis and what components are prescribed. This identified four key
themes, one of which was estimating outcome, emphasising the clinical
importance of predicting walking outcome in amputee rehabilitation.
The final section of the research took the form of an observational study
looking at the predictive nature of simple clinical tests on walking outcome
after prosthetic rehabilitation. Backward stepwise multiple linear regression
analysis resulted in a model that was able to predict 59% of the variance in
the timed up and go test and contained six predictor variables; age,
gender, amputation level, presence of contracture, ability to stand on one
leg and performance on the trail making test. If confirmed in a larger
population and across multiple sites these simple tests could be used to
improve estimation of walking outcome in the future.
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