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Review
. 2024 Nov;35(4):833-850.
doi: 10.1016/j.pmr.2024.06.005. Epub 2024 Jul 23.

Predicting Functional Outcomes Following Dysvascular Lower Limb Amputation: An Evidence Review of Personalizing Patient Outcomes

Daniel C Norvell  1 , Alison W Henderson  2 , Elizabeth G Halsne  3 , David C Morgenroth  3
Affiliations
Review

Predicting Functional Outcomes Following Dysvascular Lower Limb Amputation: An Evidence Review of Personalizing Patient Outcomes

Daniel C Norvell et al. Phys Med Rehabil Clin N Am. 2024 Nov.

Abstract

Most research on people undergoing lower limb amputations for dysvascular disease summarizes average patient outcome risks and average associations between patient factors and these outcomes. More recently, the importance of predicting patient-specific outcomes based on individual factors (ie, personalized rehabilitation) has become evident. This article reviews the evidence and discusses the importance of the following: (1) predicting outcomes to facilitate amputation-level and prosthesis prescription decisions and (2) how prediction models can be leveraged to develop decision support tools to facilitate provider/patient shared decision-making to ensure decisions considering each individual patient's priorities and preferences. Examples of these tools are discussed and referenced.

Keywords: Amputation; Decision support tools; Predicting outcomes; Prosthetics.

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Conflict of interest statement

Disclosure No authors have any commercial or financial conflicts of interest nor any funding sources to report at the time of this submission.

Figures

Fig. 1.
Fig. 1.
Example from the AMPREDICT decision support tool. (With permission from AMPREDICT.)
Fig. 2.
Fig. 2.
Example from the AMPDECIDE PtDAs. (With permission from AMPREDICT.)
Fig. 3.
Fig. 3.
Example from the amputation decision aid. (Dillon MP, Fatone S, Quigley M. (2017) A decision aid for people facing partial foot amputation due to peripheral arterial disease. http://amputationdecisionaid.com Accessed Dec 2023.)
See this image and copyright information in PMC

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