Role of Heparin to Prevent Hypertrophic Scarring in Donor Area of Split Thickness Skin Graft
Bibliographic record
Abstract
Abstract: Background: It is normal to experience hypertrophic scarring after skin harvesting at donor site. Topical heparin treatment has been suggested to have particular significance in the treatment of hypertrophic scars. Objective: to determine the effect of topical heparin for prevention of hypertrophic scars and pain status following split thickness skin graft donor site. Materials and Methods: This open label randomized control trial (NCT07196358) was performed at Plastic & Reconstructive Surgery Department, Ruth K.M. Pfau Civil Hospital, Dow University of Health Sciences during 1st August, 2024 to 31st July, 2025. Group H was assigned to heparin group whereas Group C was assigned to control group. Study outcomes included pain status, additional postoperative analgesic requirement and hypertrophic scarring. Patients were assessed at 14 days, 4 weeks, 6 weeks, 2 months and 3 months following the procedure. Result: A total 50 patients were studied in each group. Post-operative analgesic consumption was significantly lower in patients managed with heparin than control group (p<0.001). Throughout the study period pain was significantly lower in heparin group than control group. At second month and third month, occurrence of hypertrophic scarring frequency was significantly higher in control group than heparin group. The mean VSS score was significantly lower in heparin group than control group. Conclusion: The findings suggests that heparin was found to be superior in comparison to the conventional approach of sterile paraffin dressing soaked with normal saline in terms of pain control and prevention of hypertrophic scarring. Keywords: Donor site, Hypertrophic scarring, Heparin, Numeric rating scale, Vancouver scar scale, Split thickness skin graft.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".