Technological features of advanced skin protectants and an examination of the evidence base
Bibliographic record
Abstract
Products that provide a protective skin barrier play a vital role in defending the skin against the corrosive effect of bodily fluids, including wound exudate, urine, liquid faeces, stoma output and sweat. There are many products to choose from, which can be broadly categorised by ingredients. This article describes the differences in mechanisms of action between barrier products comprising petrolatum and/or zinc oxide, silicone film-forming polymers and cyanoacrylates, and compares the evidence on them. The literature indicates that all types of barrier product are clinically effective, with little comparative evidence indicating that any one ingredient is more efficacious than another, although film-forming polymers and cyanoacrylates have been found to be easier to apply and more cost-effective. However, laboratory evidence, albeit limited, indicates that a concentrated cyanoacrylate produced a more substantial and adherent layer on a porcine explant when compared with a diluted cyanoacrylate and was more effective at protecting skin from abrasion and repeated exposure to moisture than a film-forming polymer. Finally, a silicone-based cream containing micronutrients was found to significantly reduce the incidence of pressure ulceration when used as part of a comprehensive prevention strategy.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".