Use of a novel chitosan-based dressing on split-thickness skin graft donor sites: a pilot study
Bibliographic record
Abstract
OBJECTIVE: Split-thickness skin graft (STSG) donor site dressings can play an integral role in reducing donor site morbidity. This study tested a novel, chitosan-based wound dressing, Opticell Ag, as an STSG donor site dressing for wounds <10% total body surface area (TBSA). METHOD: Between January and December 2016, the chitosan-based dressing was placed on participating patients' donor sites immediately following graft harvest and covered with a transparent occlusive dressing. Pain was evaluated on postoperative day one, before dressing change between days 5-7, and before and after dressing removal between days 10-14 using the Visual Analog Scale (VAS). The extent of re-epithelialisation was determined between day 10-14 and at one month, and healing quality was also evaluated at one month post-operatively using the Vancouver Scar Scale (VSS). RESULTS: A total of 19 patients were recruited, of which 16 completed the study. Patients experienced mild-to-moderate pain in their donor sites when the chitosan-based dressing was used. Pain decreased significantly between postoperative day one and days 10-14, as well as between days 5-7 and 10-14. The mean percentage of re-epithelialisation on days 10-14 was 92% and by one month was 99%. The mean VSS at one month was 3.2±1.4. There were no statistically significant differences between patients' re-epithelialisation rates or VSS scores. There were unplanned dressing changes in four patients. No donor site infections or other adverse events were identified. CONCLUSION: The chitosan-based dressing tested in this study is safe, effective, and associated with reasonable pain control and acceptable healing quality. The results suggest that it is a promising STSG donor site dressing.
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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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".