IMPROVEMENT OF SCAR QUALITY IN SPLIT-THICKNESS SKIN GRAFT DONOR SITES: A SINGLE BLIND RANDOMIZED CLINICAL TRIAL COMPARING RIGENASE® AND POLYHEXANIDE VERSUS HYALURONIC ACID AND SILVER SULPHADIAZINE BASED DRESSINGS
Bibliographic record
Abstract
Skin graft is a reconstructive technique widely used in plastic surgery. A split-thickness skin graft (STSG) donor site represents a partial-thickness wound that is at high risk for infections, which is often underrated by healthcare practitioners. Therefore, the research of new smart dressings to achieve prompt wound healing is becoming highly important. Recently, two ad-vanced dressings for the treatment of STSG donor sites: Connettivina® Bio Plus (Fidia Farma-ceutici, S.p.A., Abano Terme, Italy) and Fitostimoline® Plus (Farmaceutici Damor, S.p.A., Napoli, Italy) are entering the market. They both favour epithelialization, which represents the main characteristic that an ideal donor site dressing should have. However, since in medical literature there is a lack of consensus about the first choice of dressing to use for STSG donor treatment, we designed a single blind randomized trial to compare these two dressings. The study included a total of 61 adult patients, all were Fitzpatrick skin type II and III. They were 59 % males and the mean age was 70.3 ± 16.5 years. Thirty three donor sites were randomized to Fitostimoline® Plus dressing and 28 to Connettivina® Bio Plus dressing. All donor sites were digitally photographed at regular intervals during the wound healing process and then 3 months later. The primary endpoint was to compare long-term scar outcome of STSG donor sites 3 months after surgery. The quality of the scar was assessed using two different scar scales: the Vancouver Scar Scale (VSS) and the Manchester Scar Scale (MSS). In both scales, a lower score means a better scar result. The average VSS total score was 3.6 for Fitostimoline Plus and 5.5 for Connettivina Bio Plus (p = 0.017). Similarly, the mean MSS total score were 7.4 for Fitostimoline Plus dressing and 9.2 for Connettivina Bio Plus dressing (p = 0.03). Both dressings showed interesting results but Fitostimoline Plus, either as impregnated gauze than as cream, demonstrated significant better scarring of the donor site. Although time to epithelialisation was similar in both the treatment groups, our results suggest that Fitostimoline Plus is better than Connettivina Bio Plus in long-term scar outcome.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".