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Record W2921468349 · doi:10.1097/won.0000000000000513

Peristomal Medical Adhesive-Related Skin Injury

2019· article· en· W2921468349 on OpenAlexaff
Kimberly LeBlanc, Ian Whiteley, Laurie McNichol, Ginger Salvadalena, Mikel Gray

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsMedicineDermatologyGeneral surgery

Abstract

fetched live from OpenAlex

Stomal and peristomal skin complications (PSCs) are prevalent in persons living with an ostomy; more than 80% of individuals with an ostomy will experience a stomal or peristomal complication within 2 years of ostomy surgery. Peristomal skin problems are especially prevalent, and a growing body of evidence indicates that they are associated with clinically relevant impairments in physical function, multiple components of health-related quality of life, and higher costs. Several mechanisms are strongly linked to PSCs including medical adhesive-related skin injuries (MARSIs). Peristomal MARSIs are defined as erythema, epidermal stripping or skin tears, erosion, bulla, or vesicle observed after removal of an adhesive ostomy pouching system. A working group of 3 clinicians with knowledge of peristomal skin health completed a scoping review that revealed a significant paucity of evidence regarding the epidemiology and management of peristomal MARSIs. As a result, an international panel of experts in ostomy care and peristomal MARSIs was convened that used a formal process to generate consensus-based statements providing guidance concerning the assessment, prevention, and treatment of peristomal MARSIs. This article summarizes the results of the scoping review and the 21 consensus-based statements used to guide assessment, prevention, and treatment of peristomal MARSIs, along with recommendations for research priorities.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.541

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 integrity0.0000.000
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 head0.005
GPT teacher head0.282
Teacher spread0.277 · 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

Citations83
Published2019
Admission routes1
Has abstractyes

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