Clinical application of skin regeneration therapy in treating skin donor site wounds
Bibliographic record
Abstract
Objective:To observe the effect of skin regeneration therapy on the healing of skin donor site wounds and to find an ideal method for improving the quality and increasing the speed of the healing of wounds.Method:Wounds in skin donor sites after harvesting 28 edge thick skin grafts (ultra-thin skin grafts),26 thin intermediate split thickness skin grafts and 18 thick intermediate split thickness skin grafts were divided randomly into 2 groups.Wounds in one group were treated with MEBO gauze and wounds in the other group treated with Vaseline gauze as a control.Pain,bleeding and wound healing time of the 2 groups were compared.Six months later,hyperplastic scars in these wounded areas were assessed using Vancouver Scar Assessment Table.Random auto control was also made.Result:In MEBO group,no pain and no bleeding occurred and the incidence of scar formation was less than that in the control group.In MEBO group,edge thick skin graft donor site wounds healed in 5.3±1.1 days,thin intermediate split thickness skin graft donor site wounds healed in 7.5±3.4 days and thick intermediate split thickness skin graft donor site wounds healed in 13.6±4.9 days.In control group,the average wound healing time was respectively 8.1±1.2 days,10.4±3.2 days and 18.5±4.2 days.The difference between the 2 groups was very significant (P＜0.01).After followed up for 6 months,in MEBO group,in intermediate split thick- ness skin graft donor sites,the scar formation assessment value was less than that in the control group (P＜0.05).Conclu- sion:MEBO gauze was superior to Vaseline gauze in treating skin donor site wounds.MEBO has bleeding stopping,pain re- lieving and wound healing promoting effects.The wounds healed by physiological regeneration without marked formation of scars.MEBO gauze treatment is an ideal method for promoting skin donor site wound healing,especially intermediate split thickness skin graft donor site wounds.It can improve the quality of wound healing and shorten healing time.
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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 | 0.000 |
| 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) | 0.003 | 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".