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Record W4400768475 · doi:10.1016/j.jtv.2024.07.003

The development of international wound debridement best practice recommendations: Consensus between nurses specialized in Wound, Ostomy and Continence Canada and the society of tissue viability

2024· article· en· W4400768475 on OpenAlexaffabout
Kimberly LeBlanc, Mary C. Hill, Erin M. Rajhathy, Nancy Parslow, Clare Greenwood, Joshua T. Swan, Sharon Neill, Ina Farrelly, Catherine Harley

Bibliographic record

VenueJournal of Tissue Viability · 2024
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsMedicineDebridement (dental)Wound careScope (computer science)Intensive care medicineSurgical debridementScope of practiceNursingHealth careSurgery

Abstract

fetched live from OpenAlex

Debridement is an important component of wound management and can improve outcomes for patients. Debridement needs to be done by an appropriately trained health professional, but the scope of practice, credentials, training, competencies, and regulatory requirements regarding wound debridement can differ. Best Practice Recommendations were created to positively influence patient safety related to all methods of debridement, across the continuum of care, and to be implemented widely by nurses at all professional levels in Canada. AIM: To further develop the Best Practice Recommendations for wound debridement, with an international perspective, by creating a consensus document to support the global adoption of evidence-based debridement practice for health professionals. METHODS: A consensus meeting utilising Delphi methods was conducted between the authors to review the consensus statements. Once 80 % agreement was achieved, a wide range of wound care experts were identified by the authors and invited to participate in an external review of the statements. RESULTS: Fifteen consensus statements about wound debridement were agreed upon and are presented in this paper. CONCLUSIONS: These best practice recommendations have been reviewed by a wide range of practitioners from across the UK and Canada and aim to provide guidance on the standardisation of debridement practices for healthcare professionals.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 integrity0.0000.000
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 head0.026
GPT teacher head0.360
Teacher spread0.334 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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