Outcomes of the Use of Hyaluronic Acid-Based Wound Dressings for the Treatment of Partial-Thickness Facial Burns
Bibliographic record
Abstract
The purpose of this study was to assess clinical, functional and cosmetic outcomes of the use of hyaluronic acid-based wound dressings for partial-thickness facial burns. Patients with partial-thickness facial burns hospitalized at the Burn Center between April 2014 and April 2017 were evaluated. Data pertaining to demographic characteristics, etiology, and degree of burn and percentage of burn to TBSA were collected. Pain, infection rates, reapplication rates, length of hospital stay, duration of healing, and presence of scar formation were analyzed. Median percentage of burn to TBSA was 15% (interquartile range [IQR]: 9-20). Fifteen patients had only facial burns, while 39 patients had burns on other parts of the body in addition to the face. Nine patients had deep partial-thickness burns, while 45 had superficial partial-thickness burns. Median length of hospital stay was 7 days (IQR: 3-15) for the entire study population and 4 days (IQR: 2-7.5) for patients who had only facial burns. Median healing time was 9 days (IQR: 7-12). Fifty-one (94%) patients had a Vancouver Scar Scale score of zero at 6 months. Use of hyaluronic acid-based wound dressings for facial burns is an effective and safe option.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".