Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules

Questions: Can rules be developed to predict the risk of non-use of prostheses by people with lower limb amputation following discharge from rehabilitation? Are these clinical prediction rules valid? Design: Retrospective and prospective cohort study designs. Participants: Consecutive tertiary rehab...

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Main Authors: Roffman, Caroline, Buchanan, John, Allison, Garry
Format: Journal Article
Published: Australian Physiotherapy Association 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/28983
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author Roffman, Caroline
Buchanan, John
Allison, Garry
author_facet Roffman, Caroline
Buchanan, John
Allison, Garry
author_sort Roffman, Caroline
building Curtin Institutional Repository
collection Online Access
description Questions: Can rules be developed to predict the risk of non-use of prostheses by people with lower limb amputation following discharge from rehabilitation? Are these clinical prediction rules valid? Design: Retrospective and prospective cohort study designs. Participants: Consecutive tertiary rehabilitation patients: 135 retrospective (103 males, mean age = 56 years, SD 15) and 66 prospective (58 males, mean age = 54 years, SD 16). Method: Medical records were audited for potential predictor variables. Retrospective participants were interviewed at a median of 1.9 years after discharge (IQR 1.4 to 2.5) and prospective participants at a median of 1.3 years (IQR 1.1 to 1.4). Results: Clinical prediction rules were identified at 4, 8 and 12 months after discharge, and validated. Amputation levels above transtibial and mobility-aid use were common predictors for all three time frames. At 4 months, if four out of five predictor variables were present (LR+ = 43.9, 95% CI 2.73 to 999+), the probability of non-use increased from 12 to 86% (p < 0.001). At 8 months, if all three predictor variables were present (LR+ = 33.9, 95% CI 2.1 to 999+), the probability of non-use increased from 15 to 86% (p < 0.001). At 12 months, if two out of three predictor variables were present (LR+ = 2.8, 95% CI 0.9 to 6.6), the probability of non-use increased from 17 to 36% (p < 0.031). Conclusions: These validated clinical prediction rules have implications for rehabilitation and service model development.
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spelling curtin-20.500.11937-289832017-09-13T15:19:07Z Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules Roffman, Caroline Buchanan, John Allison, Garry Rehabilitation outcome Amputation Lower extremity Clinical prediction rule Leg prosthesis Questions: Can rules be developed to predict the risk of non-use of prostheses by people with lower limb amputation following discharge from rehabilitation? Are these clinical prediction rules valid? Design: Retrospective and prospective cohort study designs. Participants: Consecutive tertiary rehabilitation patients: 135 retrospective (103 males, mean age = 56 years, SD 15) and 66 prospective (58 males, mean age = 54 years, SD 16). Method: Medical records were audited for potential predictor variables. Retrospective participants were interviewed at a median of 1.9 years after discharge (IQR 1.4 to 2.5) and prospective participants at a median of 1.3 years (IQR 1.1 to 1.4). Results: Clinical prediction rules were identified at 4, 8 and 12 months after discharge, and validated. Amputation levels above transtibial and mobility-aid use were common predictors for all three time frames. At 4 months, if four out of five predictor variables were present (LR+ = 43.9, 95% CI 2.73 to 999+), the probability of non-use increased from 12 to 86% (p < 0.001). At 8 months, if all three predictor variables were present (LR+ = 33.9, 95% CI 2.1 to 999+), the probability of non-use increased from 15 to 86% (p < 0.001). At 12 months, if two out of three predictor variables were present (LR+ = 2.8, 95% CI 0.9 to 6.6), the probability of non-use increased from 17 to 36% (p < 0.031). Conclusions: These validated clinical prediction rules have implications for rehabilitation and service model development. 2014 Journal Article http://hdl.handle.net/20.500.11937/28983 10.1016/j.jphys.2014.09.003 Australian Physiotherapy Association fulltext
spellingShingle Rehabilitation outcome
Amputation
Lower extremity
Clinical prediction rule
Leg prosthesis
Roffman, Caroline
Buchanan, John
Allison, Garry
Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title_full Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title_fullStr Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title_full_unstemmed Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title_short Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
title_sort predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules
topic Rehabilitation outcome
Amputation
Lower extremity
Clinical prediction rule
Leg prosthesis
url http://hdl.handle.net/20.500.11937/28983