In Vivo Study of Wound Bursting Strength and Compliance of Topical Skin Adhesives
Bibliographic record
Abstract
OBJECTIVES: Over the past decade, the use of topical skin adhesives (TSA) for wound closure has increased. Among TSA characteristics, strength and flexibility are most important. Prior studies have compared the wound bursting strengths (WBSs) of the cyanoacrylates immediately after wound closure. In this study the authors compared the WBS and flexibility of multiple TSAs immediately and up to 2 days after closure. METHODS: This was a controlled animal experiment. Two-centimeter incisions were created on both sides of 210 Sprague-Dawley rats and randomly closed with one of five commercially available TSAs (Dermabond [D], Indermil [I], Histoacryl [H], Liquiband [L], or GluStitch [G]). WBS and TSA flexibility were measured using the BTC-2000 device immediately after closure and at 1 and 2 days after closure. WBS and TSA flexibility were compared across groups with analysis of variance (ANOVA). RESULTS: Wound bursting strengths were higher (p < 0.05) at 0, 1, and 2 days for D (274, 388, 232 mm Hg) than for all other TSAs (I 182, 225, and 107; H 189, 214, and 69; L 146, 118, and 75; or G 161, 150, and 73). TSA flexibility was also greater (p < 0.05) at 0, 1, and 2 days for D (36, 27, and 29 mm Hg/mm) than for all other TSAs (I 18, 14, and 12; H 18, 13, and 15; L 19, 14, and 12; G 26, 23, and 18). CONCLUSIONS: The octyl-cyanoacrylate-based adhesive is significantly stronger and more flexible than all the butyl-cyanoacrylate-based adhesives at 0, 1 and 2 days after closure.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".