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Record W3025130957 · doi:10.33137/cpoj.v3i1.33916

COMORBIDITY AND NON-PROSTHETIC INPATIENT REHABILITATION OUTCOMES AFTER DYSVASCULAR LOWER EXTREMITY AMPUTATION

2020· article· en· W3025130957 on OpenAlexaffvenueabout
Michelle G. Marquez, Matthew Kowgier, W. Shane Journeay

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsToronto Rehabilitation InstituteProvidence Health CarePublic Health OntarioUniversity of TorontoMcGill University
Fundersnot available
KeywordsAmputationComorbidityRehabilitationMedicinePhysical therapyPhysical medicine and rehabilitationSurgeryPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Dysvascular amputations arising from peripheral vascular disease and/or diabetes are common. Patients who undergo amputation often have additional comorbidities that may impact their recovery after surgery. Many individuals undergo post-operative inpatient rehabilitation to improve their non-prosthetic functional independence. Thus far, our characterization of comorbidity in this population and how it is associated with non-prosthetic inpatient functional recovery remains relatively unexplored. OBJECTIVE: The objective of this study was to describe comorbidities, using the Charlson Comorbidity Index (CCI), and to examine associations between comorbidity and functional outcomes in a cohort of patients with dysvascular limb loss undergoing non-prosthetic inpatient rehabilitation. METHODOLOGY: A retrospective cohort design was used to analyze a group of 143 patients with unilateral, dysvascular limb loss who were admitted to inpatient rehabilitation. Age, sex, amputation level, amputation side, length of stay (LOS), time since surgery, Functional Independence Measure (FIM) scores (Total and Motor at admission and discharge), and CCI scores were collected. FINDINGS: The data showed that neither total or specific comorbidities were associated with functional outcomes or LOS in this cohort and rehabilitation model. Multivariate analysis demonstrated an inverse relationship with age and FIM scores, where increased age was associated with lower Total and Motor FIM at admission and discharge. Comorbidities were not associated with functional outcomes. Dementia was negatively associated with FIM scores, however this requires more study given the low number of patients with dementia in this cohort. CONCLUSION: These data suggest that regardless of burden of comorbidity or specific comorbidities that patients with dysvascular limb loss may derive similar functional benefit from post-operative non-prosthetic inpatient rehabilitation. Layman’s Abstract: Lower extremity limb loss arising from peripheral vascular disease and/or diabetes is common. Patients who require amputation often have multiple medical conditions that may impact their recovery after surgery. Moreover, many individuals undergo inpatient rehabilitation after surgery to improve self-care and mobility before discharge from hospital. We understand very little about how multiple medical conditions in patients with recent limb loss who are admitted to rehabilitation hospitals are impacted. Specifically, whether individuals with multiple medical conditions have negative functional consequences and do they stay in a rehabilitation hospital for a longer period of time. The objective of this study was to describe the types of medical conditions that patients with recent limb loss have and to examine the relationship between these conditions with functional outcomes and length of stay in hospital while undergoing inpatient rehabilitation. 143 patients with unilateral, dysvascular limb loss who were admitted to an inpatient rehabilitation hospital were included in the analysis. Age, gender, amputation level, amputation side, length of stay, time since surgery, Functional Independence Measure scores (measure of a patient’s function) and Charlson Comorbidity Index (measure of multiple medical conditions) scores were collected. This study suggests that regardless of the burden of multiple medical conditions or specific medical problems, that patients with recent limb loss may derive similar benefit after surgery at an inpatient rehabilitation hospital prior to consideration for a prosthesis. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/33916/26327 How To Cite: Marquez M.G., Kowgier M., Journeay W.S. Comorbidity and non-prosthetic inpatient rehabilitation outcomes after dysvascular lower extremity amputation. Canadian Prosthetics & Orthotics Journal. 2020;Volume3, Issue1, No.1. https://doi.org/ 10.33137/cpoj.v3i1.33916 Corresponding Author: Dr. W. Shane Journeay, PhD, MD, MPH, FRCPC, BC-Occ MedProvidence Healthcare – Unity Health Toronto, 3276 St Clair Avenue East, Toronto ON M1L 1W1E-mail: shane.journeay@utoronto.caORCID: https://orcid.org/0000-0001-6075-3176

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.189
Teacher spread0.184 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2020
Admission routes3
Has abstractyes

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