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

    219310_139106_1-s2.0-S1836955314001271-main.pdf (299.6Kb)
    Access Status
    Open access
    Authors
    Roffman, Caroline
    Buchanan, John
    Allison, Garry
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Roffman, C. and Buchanan, J. and Allison, G. 2014. Predictors of non-use of prostheses by people with lower limb amputation after discharge from rehabilitation: development and validation of clinical prediction rules. Journal of Physiotherapy. 60 (4): pp. 224-231.
    Source Title
    Journal of Physiotherapy
    DOI
    10.1016/j.jphys.2014.09.003
    ISSN
    1836-9553
    School
    School of Physiotherapy and Exercise Science
    Remarks

    This open access article is distributed under the Creative Commons license http://creativecommons.org/licenses/by-nc-nd/3.0/

    URI
    http://hdl.handle.net/20.500.11937/28983
    Collection
    • Curtin Research Publications
    Abstract

    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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