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Record W3166250738 · doi:10.33137/cpoj.v4i1.35098

SELF-MANAGEMENT IN PERSONS WITH LIMB LOSS: A SYSTEMATIC REVIEW

2021· review· en· W3166250738 on OpenAlexvenueaboutno aff
Daniel Joseph Lee, Theresa Repole, Emily Taussig, Stephanie Edwards, Jamie Misegades, J Gomes Guerra, Amira Lisle

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2021
Typereview
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsLimb lossPhysical medicine and rehabilitationPsychologyMedicineSurgeryAmputation

Abstract

fetched live from OpenAlex

BACKGROUND: Self-management is an integral component of managing long-term conditions and diseases. For a person with limb loss, this self-management process involves caring for the residual limb, the prosthesis, and the prosthetic socket-residual limb interface. Failure to properly self-manage can result in unwanted secondary complications such as skin breakdown, falls, or non-use of the prosthesis. However, there is little evidence on what self-management interventions are effective at preventing secondary complications. To understand the impact of self-management after the loss of a limb, it is necessary to determine what the current evidence base supports.
 OBJECTIVE(S): The purpose of this study is to examine the available literature on self-management interventions and/or outcomes for persons with limb loss and describe how it may impact residual limb health or prosthesis use.
 METHODOLOGY: A systematic review of multiple databases was carried out using a variety of search terms associated with self-management. The results were reviewed and selected based on the inclusion criteria: self-management interventions or direct outcomes related to self-management, which includes the skin integrity of the residual limb, problem-solving the fit of the prosthesis, and education in the prevention of secondary complications associated with prosthesis use. The Cincinnati Childrens’ LEGEND (Let Evidence Guide Every New Decision) appraisal forms were used to analyze the articles and assign grades.
 FINDINGS: Out of the 40 articles identified for possible inclusion in this study, 33 were excluded resulting in seven articles being selected for this review. Three out of the seven articles focused on silicone liner management while the other four articles focused on skin issues.
 CONCLUSION: Self-management for a person with limb loss is a key component of preventing complications associated with loss of limb and prosthesis use. There is a lack of high-quality experimental studies exploring the most appropriate intervention for teaching self-management when compared to other conditions, specifically diabetes. Further research in the area of self-management is necessary to understand how to best prevent unwanted secondary complications.
 Layman's Abstract
 Self-management is an integral component of managing long-term conditions and diseases. Self-management for a person with limb loss involves performing proper hygiene of the residual limb, caring for the prosthesis, and problem-solving the fit between the prosthetic socket and the residual limb. If a person with limb loss fails to correctly self-manage, they may be exposing themselves to the risk of skin breakdown or injury. Other medical diagnoses like diabetes emphasize self-management in the care of persons with the condition and have established a large body of knowledge surrounding this element of lifestyle adaption. However, in the case of limb loss, there is very little evidence to support how self-management is taught or performed. Therefore, the purpose of this study was to explore the body of literature surrounding self-management in persons with limb loss. The results indicate that there is very little evidence supporting self-management related interventions and that further research is required in this area. With the addition of further research, clinical practice can be improved and self-management interventions can become standardized across the spectrum of care, much like in diabetes care.
 Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/35098/27909
 How To Cite: Lee DJ, Repole T, Taussig E, Edwards S, Misegades J, Guerra J, Lisle A. Self-management in persons with limb loss: A systematic review. Canadian Prosthetics & Orthotics Journal. 2021;Volume 4, Issue 1, No.5. https://doi.org/10.33137/cpoj.v4i1.35098
 Corresponding Author: Daniel J. Lee, PT, PhD, DPT, GCS, COMTTouro College, Department of Physical Therapy, Bayshore, NY USA.Email:Daniel.lee29@touro.edu ORCID: https://orcid.org/0000-0003-1805-2936

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.243
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes2
Has abstractyes

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