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Record W4386711469 · doi:10.12688/hrbopenres.13739.1

A protocol for a scoping review to identify methods used in clinical practice to assess wound odour

2023· review· en· W4386711469 on OpenAlexaff
Georgina Gethin, Kimberly LeBlanc, John D. Ivory, Caroline McIntosh, Damien Pastor, Enda Naughten, Chloe Hobbs, Barry M. McGrath, Stephen Cunningham, Lokesh Joshi, Suzanne Moloney, Sebastian Probst

Bibliographic record

VenueHRB Open Research · 2023
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsMcGill University
FundersHealth Research Board
KeywordsProtocol (science)Wound careMedicineComputer scienceIntensive care medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

<ns3:p> <ns3:bold>Objective:</ns3:bold> The objective of this scoping review is to map, from wound assessment tools and other literature, the current methods used to assess wound odour in order to answer the following question: Which methods of assessment, validated or otherwise, are currently used in wound assessment tools to assess wound odour? </ns3:p> <ns3:p> <ns3:bold>Introduction:</ns3:bold> Wound assessment includes not only details of the condition of the wound bed but also evaluation of symptoms associated with the wound including that of odour. Odour is cited by clinicians, patients and carers as one of the most distressing wound symptoms. However, there is no consensus on a preferred method to assess odour thus negatively impacting the internal and external validity of many clinical trials and minimising the ability to perform meta-analysis. </ns3:p> <ns3:p> <ns3:bold>Eligibility criteria:</ns3:bold> Any wound assessment tool or framework that includes assessment of wound odour in any wound aetiology and in any care setting. Any systematic or scoping review that includes assessment of wound odour in any wound aetiology and in any care setting. No limits on date of publication or language will be applied. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> We will employ the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines for this scoping review and base its structure on the framework proposed by Arksey and O’Malley. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> A narrative format will summarise extracted data and provide an overview of tools used to assess wound odour. A PRISMA diagram will outline the results of the search strategy. The identified tools will be summarised in table format and stratified according to methods used. </ns3:p> <ns3:p> <ns3:bold>Conclusion:</ns3:bold> The result of this scoping review will be a list of methods used to assess odour in wounds and will be used to inform a subsequent Delphi study to gain consensus on the preferred method to assess wound odour. </ns3:p>

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)0.070
metaresearch head score (Gemma)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0700.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.964
GPT teacher head0.848
Teacher spread0.116 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreProtocol

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

Citations0
Published2023
Admission routes1
Has abstractyes

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