Bibliographic record
Abstract
Current wound management through the use of a split-thickness skin graft often requires hospital admission, a period of immobility, attentive donor site wound care and pain management. This study evaluates the feasibility of using a novel epidermal graft-harvesting device (CelluTome) that allows pain-free epidermal skin grafting in the outpatient clinic setting. A prospective series of 35 patients was performed in 2 centres, involving 10 acute and 25 chronic wounds. All patients were subjected to epidermal grafting in the outpatient specialist clinic, without the use of anaesthesia, and allowed to return home after the procedure. Completely healed wounds were noted in 22 patients (62·9%). The overall mean time for 50% and 100% reduction in wound size was 3·31 ± 2·33 and 5·91 ± 3·48 weeks, respectively. There was no significant difference in healing times between the acute and chronic wounds (50% reduction in wound size; acute 2·20 ± 0·91 weeks versus chronic 3·73 ± 2·63 weeks, P = 0·171. Hundred percent reduction in wound size; acute 4·80 ± 1·61 weeks versus chronic 6·83 ± 4·47 weeks, P = 0·183). The mean time for donor site healing was 5·49 ± 1·48 days. The mean pain score during graft harvest was 1·42 ± 0·95, and the donor site Vancouver Scar Scale was 0 for all cases at 6 weeks. This automated device offers autologous skin harvesting in the outpatient setting with minimal or no pain and a scar free donor site, equally benefiting both the acute and chronic wounds. It has the potential to save NHS resources by eliminating the need for theatre space and a hospital bed while at the same time benefiting patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.132 | 0.004 |
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; both teacher heads agree on what is shown here.
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".