A Concave Shaped Skin Barrier Provides Improved Clinical Outcomes for People Living With an Ostomy Who Have an Outward Peristomal Body Profile
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".