Dermal Substitution in Acute Burns and Reconstructive Surgery: A Subjective and Objective Long-Term Follow-Up
Bibliographic record
Abstract
Tissue engineering and dermal substitution are currently prominent topics of wound-healing research. However, no extensive clinical trials with objective evaluation criteria have been published so far that support the clinical effectiveness of dermal equivalents in the long term. The dermal substitute that is discussed here is derived from bovine collagen and elastin-hydrolysate and has been shown to improve skin elasticity during a short-term clinical follow-up of scar reconstructions. In this study we will present the long-term outcome by means of objective and subjective scar assessment tools for dermal substitution in acute burn wounds and scar reconstructions. In a clinical trial, an intraindividual comparison was performed between the conventional split-thickness autograft and a combination of the collagen/elastin substitute with an autograft. After 1 year, scars were evaluated by the Cutometer SEM 474 for objective elasticity measurements and by planimetry to establish scar contraction. An independent observer subjected scars to a generally accepted clinical scar assessment tool: the Vancouver Scar Scale. In addition, patients gave their impression of the outcome. Forty-two paired burn wounds and 44 paired scar reconstructions were included and evaluated 1 year after surgery. Although substituted scar reconstructions demonstrated an elasticity improvement of approximately 20 percent compared with control wounds, no statistically significant differences were found for skin elasticity, scar contraction, Vancouver Scar Scale, and patient's impression in both categories after 1 year. An extensive long-term follow-up shows that the dermal substitute, which was proven effective in a clinical trial on a short-term basis, did not yield statistical evidence for a long-term clinical effectiveness of dermal substitution.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".