Reconstruction of Burn Scar of the Upper Extremities with Artificial Skin
Bibliographic record
Abstract
The management of upper-extremity burn contractures is a major challenge for plastic surgeons. After approval by the Food and Drug Administration, artificial skin (Integra) has been available in Taiwan since 1997. From January of 1997 to July of 1999, the authors applied artificial skin to 13 severely burned patients for the reconstruction of their upper extremities, resulting in an increased range of motion in the upper-extremity joints and improved skin quality. An additional benefit was the rapid reepithelialization of the donor sites. There were no complications of infection throughout the therapeutic course, and the overall results were satisfactory. During the 2-year study, scar condition was monitored between 8 and 24 months, and a good appearance and pliable skin were obtained according to the Vancouver Scar Scale. According to this evaluation of Oriental skin turgor, normal pigmentation was restored about 6 months after the resurfacing procedure. For patients with severe burns in whom there is insufficient available skin for a full-thickness skin graft or another appropriate flap for scar revision, Integra is an alternative. The two major concerns in dealing with artificial skin are (1) a 10- to 14-day waiting period for maturation of the neo-dermis, necessitating a two-stage operation, and (2) prevention of infection with antibiotics and meticulous wound care.
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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 | 0.001 |
| 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".