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Record W4408884097 · doi:10.1097/won.0000000000001155

A Concave Shaped Skin Barrier Provides Improved Clinical Outcomes for People Living With an Ostomy Who Have an Outward Peristomal Body Profile

2025· article· en· W4408884097 on OpenAlexaffabout
Diane St-Cyr, Danielle Gilbert, Isabelle Dionne, Matthew T. Kelly, Natalie Kameka

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsCARE CanadaInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsMedicineUsabilityMulticenter studySurgeryRandomized controlled trial

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to compare leakage rates, skin health, fit, patient impact and usability for a concave ostomy system versus the non-concave ostomy system subjects were using prior to the study. DESIGN: Single-arm, open-label, multicenter, prospective study with subjects acting as their own control. SUBJECTS AND SETTING: The sample comprised 20 subjects recruited from 3 outpatient clinics in Quebec, Canada. All participants were adults with an ostomy and had an outward peristomal body profile (OPBP). METHODS: Data were collected by investigators during in-person visits. Skin health was assessed using the Ostomy Skin Tool. Patient-reported outcomes were collected at each visit using a questionnaire designed for this study. Investigator-reported observations were also collected using a study-specific questionnaire at each visit. Generalized linear mixed model analyses were used to analyze the data. RESULTS: Use of the concave skin barrier significantly reduced leakage occurrences, improved peristomal skin health, provided a better fit, enhanced the users' sense of security, comfort, and ease of application of the concave pouching system when compared to a flat or convex skin barrier. CONCLUSIONS: The use of a concave ostomy system for patients with an OPBP significantly reduced leakage while improving skin health, fit, patient impact and usability.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.350
Teacher spread0.331 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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