Factors that predict walking ability with a prosthesis in lower limb amputees
Introduction. Identification of predictive factors for walking ability with a prosthesis, after lower limb amputation, is very important in order to define patient’s potentials and realistic rehabilitation goals, however challenging they are. Objective. The objective of this study was to in...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Serbian Medical Society
2016-01-01
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| Series: | Srpski Arhiv za Celokupno Lekarstvo |
| Subjects: | |
| Online Access: | http://www.doiserbia.nb.rs/img/doi/0370-8179/2016/0370-81791610507K.pdf |
| Summary: | Introduction. Identification of predictive factors for walking ability with a
prosthesis, after lower limb amputation, is very important in order to define
patient’s potentials and realistic rehabilitation goals, however challenging
they are. Objective. The objective of this study was to investigate whether
variables determined at the beginning of rehabilitation process are able to
predict walking ability at the end of the treatment using support vector
machines (SVMs). Methods. This research was designed as a retrospective
clinical case series. The outcome was defined as three-leveled ambulation
ability. SVMs were used for predicting model forming. Results. The study
included 263 patients, average age 60.82 Ѓ} 9.27 years. In creating SVM
models, eleven variables were included: age, gender, cause of amputation,
amputation level, period from amputation to prosthetic rehabilitation,
Functional Comorbidity Index (FCI), presence of diabetes, presence of a
partner, restriction concerning hip or knee extension, residual limb hip
extensor strength, and mobility at admission. Six SVM models were created
with four, five, six, eight, 10, and 11 variables, respectively. Genetic
algorithm was used as an optimization procedure in order to select the best
variables for predicting the level of walking ability. The accuracy of these
models ranged from 72.5% to 82.5%. Conclusion. By using SVM model with four
variables (age, FCI, level of amputation, and mobility at admission) we are
able to predict the level of ambulation with a prosthesis in lower limb
amputees with high accuracy. |
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| ISSN: | 0370-8179 2406-0895 |