The comparative study on the effect of one-stage skin graft and VSD treatment of second-stage sugery after scar release
Bibliographic record
Abstract
Objective To investigate the difference of vacuum sealing drainage (VSD) on the effect of one-stage skin graft and second-stage sugery after scar release. Methods A total of 42 patients who wanted to undergo scar release and skin graft was randomly divided to control group (n=21) and VSD treatment group (n=21). The control group implemented skin graft immdiately after scar release while VSD treatment group were treated with VSD for 3 days after scar release and then implemented skin graft. The rate of subcutaneous blood stasis and the survival rate of skin graft were observed at 7 days after skin graft. The condition of grafted skin contracture and hyperplasia after half a year was also observed. Results The incidence of subcutaneous blood stasis was significantly lower in the VSD group than that in the control group (P<0.05). The survival rate of skin grafts was significantly higher in the VSD group than that of the control group (P<0.05). The score of Vancouver scar was significantly lower in the VSD group than that in the control group (P<0.05). Conclusions VSD treatment of second-stage sugery after scar release can reduce the occurrence of subcutaneous blood stasis, promote skin graft survival, reduce postoperative skin graft contracture and improve the prognosis of patients compared to one-stage skin graft. Key words: Cicatrix/SU; Negative-pressure wound therapy; Skin transplantation; Drainage
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".