Utility of RECELL® for Traumatic Skin Defects: A Study Protocol (Preprint)
Bibliographic record
Abstract
BACKGROUND RECELL® (Avita Medical, Cambridge, UK), a non-cultured skin cell suspension technique, provides results comparable with skin grafting in terms of duration and healing quality. However, in Japan, the clinical use of RECELL® for burn trauma has become possible but not for skin defects associated with trauma. Reports using RECELL® with split-thickness skin grafting for burn trauma showed good results. OBJECTIVE The purpose of this study is to evaluate the utility of the RECELL® skin reconstruction technique in trauma cases with significant skin defects. METHODS Methods This is a single-center, open-label, uncontrolled, single-arm comparative prospective study. The inclusion criteria are age ≥ 16 years with skin defects ≥ 160 cm2 due to trauma (excluding the hands and face and burn trauma) or skin defects due to skin flaps. The test site should exhibit sufficient dermal-like tissue formation. Under general anesthesia, skin grafts will be harvested from healthy skin donor sites (groin, thigh, or scalp). In addition to RECELL® skin grafts, the necessary amount of mesh skin grafts will be collected. A mesh graft will be applied to the defect where the graft is to be placed, and the non-cultured cell suspension previously prepared using the RECELL® technique will be sprayed onto the mesh grafted area. A non-adherent gauze will be applied to the skin graft, and the gauze will be placed over the gauze for bandage fixation. The primary endpoints are healing of the recipient and donor sites. The secondary endpoints are scar assessment using the Vancouver Scar Scale, pigmentation, vascularity, pliability, and contracture. The observation period will be 24 weeks after surgery. RESULTS - CONCLUSIONS We intend to validate the utility of RECELL® for skin defects due to trauma by observing wound closure, scar formation including its adverse events, delayed healing, infection, and its durability. CLINICALTRIAL
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".