Investigating the Impact of Wound Edge Approximation With Skin Grafting on Hypertrophic Scar Reduction: A Randomized Controlled Clinical Trial
Bibliographic record
Abstract
In modern burn care, the focus extends beyond mere patient survival to encompass long-term functional and cosmetic outcomes. Research suggests that the technique and manner of suturing during skin grafting play a significant role in scar formation. This study aimed to explore the effectiveness of wound edge approximation with skin grafting compared to the conventional approach, where the graft edge exclusively interacts with the wound edge, in reducing hypertrophic scar development. Seventy-four burn unit patients eligible for grafting were randomly allocated into 2 groups: those receiving grafts with overlapping edges (Group A) and those receiving grafts with edges tailored to the burn wound (Group B). Evaluation of graft sites occurred immediately post-surgery and at 1 and 6 months post-operatively using the standardized Vancouver Scar Scale (VSS) administered by trained surgeons. The findings of this study revealed that there was no statistically significant difference between the 2 examined groups regarding the average duration of hospitalization and the mean thickness of wounds (P > 0.05). Similarly, the mean scores for pain, vascular index, and pigmentation index immediately post-surgery, at 1 month, and 6 months later, as well as the scar height index and flexibility immediately and at 1-month post-surgery, and the VSS index at the study's conclusion, showed no significant variation between the 2 groups (P > 0.05). However, at the 6-month follow-up, the mean scar height score (P = 0.004) in the overlapping group and the mean flexibility score (P = 0.017) in the non-overlapping group were significantly lower compared to the respective alternative group. This indicates a notable improvement in scar height and wound flexibility in the overlapping group over the non-overlapping group after 6 months.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".