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Record W4405098364 · doi:10.1016/j.jtv.2024.12.009

Adults living with dementia and chronic wounds, wound types, care challenges, and impact across dementia stages: A scoping review protocol

2024· review· en· W4405098364 on OpenAlexaff
Kimberly LeBlanc, Kevin Woo, Georgina Gethin, Dimitri Beeckman, Corey Heerschap, Madhuri Reddy, Christina Parker, Margaret MacAndrew, Foy White-Chu, Samantha Wiesenfeld

Bibliographic record

VenueJournal of Tissue Viability · 2024
Typereview
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsMcGill University Health CentreRoyal Victoria Regional Health CentreSKiN Health
Fundersnot available
KeywordsMedicineDementiaProtocol (science)Wound careGerontologyIntensive care medicineAlternative medicinePathologyDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to map the existing evidence on the epidemiology, care challenges, and impacts of various wound types among individuals living with dementia across different stages of the disease. INTRODUCTION: Dementia is a growing global health concern, projected to rise significantly as the population ages. This condition not only affects cognitive function but also increases the risk of chronic wounds in part due to impairments in mobility, self-care, and communication. Current wound care guidelines inadequately address the specific needs of individuals with dementia. This scoping review seeks to fill this gap by comprehensively exploring the intersection between dementia and wound care. INCLUSION CRITERIA: This review will include studies involving adults aged 18 and older diagnosed with dementia or cognitive impairment who are experiencing alterations in skin integrity, such as pressure injuries, venous and arterial ulcers, and diabetic ulcers. Both qualitative and quantitative studies will be considered, as well as studies focusing on the challenges faced by caregivers in managing wounds in this population. Excluded are studies such as editorials and opinion articles. METHODS: A comprehensive search strategy will be employed across multiple electronic databases, including MEDLINE, CINAHL, PsycINFO, EMBASE, and PubMed, as well as grey literature sources like ProQuest Dissertations & Theses Global and OpenGrey. The search will include studies published in English and French without date restrictions. Data will be extracted using a pilot-tested tool and presented in graphical, diagrammatic, and tabular formats. A narrative summary will accompany these visuals, providing context and insights into the data in relation to the review's objectives.

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)0.004
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.539
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.068
GPT teacher head0.494
Teacher spread0.426 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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