A Pilot Study to Evaluate the Minimally Invasive Burn Care for Small, Deep Partial-Thickness Burns of the Hands and Feet Using Enzyme Debridement and Autologous Skin Cell Spray
Bibliographic record
Abstract
Background/Objectives: We treated deep partial-thickness burns of the hands and feet in four cases using a combination of NexoBrid and ReCell autologous cell regeneration techniques, without conventional split-thickness skin graft, with good results following debridement of the eschar. Methods: We report cases of patients treated with a combination of the NexoBrid and ReCell techniques between 1 August 2023 and 31 July 2024. The degree of debridement and the time to complete wound closure were evaluated. Scar quality was assessed using the Vancouver Scar Scale (VSS). Results: Four patients aged 0–28 years with an average total burn surface area of 1.2% were treated on two hands and two feet, with an average follow-up of 12 months; no additional surgical treatment was needed. The mean VSS score was 0.25. The patients were satisfied with the aesthetic appearance of their hands and feet, and no complications, such as hypertrophic scars, were observed. We also developed separate algorithms for sedation and analgesia management for adults and children. Conclusions: Using ReCell alone following debridement of small burn wounds with NexoBrid resulted in early wound closure with good scar condition and cosmetic appearance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".