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Results of the 2022 Wound Survey on Skin Failure/End-of-Life Terminology and Pressure Injuries

2023· article· en· W4321381741 on OpenAlexaff
R. Gary Sibbald, Elizabeth A. Ayello

Bibliographic record

VenueAdvances in Skin & Wound Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsTerminologyMedicineSurvey researchStatement (logic)Coronavirus disease 2019 (COVID-19)PathologyDiseaseApplied psychologyPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize the major findings of a survey first conducted in 2019 and repeated in 2022 and review new concepts (angiosomes and pressure injuries) and challenges due to the COVID-19 pandemic. METHODS: This survey captures participants' ranking of agreement or disagreement with 10 statements on Kennedy terminal ulcers, Skin Changes At Life's End, Trombley-Brennan terminal tissue injuries, skin failure, and unavoidable/avoidable pressure injuries. The survey was hosted online by SurveyMonkey from February 2022 until June 2022. All interested persons were able to participate in this voluntary, anonymous survey. RESULTS: Overall, 145 respondents participated. The same nine statements achieved at least 80% agreement (somewhat agree or strongly agree) as in the previous survey. The one statement that did not reach consensus also failed to reach consensus in the 2019 survey: "The concept of skin failure does not include pressure injuries." CONCLUSIONS: It is the authors' hope that this will stimulate more research into terminology and etiology of skin changes in persons at end of life and encourage more research regarding terminology and criteria to define which skin lesions are unavoidable or avoidable.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.031
GPT teacher head0.386
Teacher spread0.355 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2023
Admission routes1
Has abstractyes

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