Mechanomodulation of Burn Scarring Via Pressure Therapy
Bibliographic record
Abstract
Significance: The physical and psychological sequalae of burn injuries account for 10 million disability-adjusted life years lost annually. Hypertrophic scarring (HSc) after burn injury results in reduced mobility, contracture, pain, itching, and aesthetic changes for burn survivors. Despite the prevalence of scarring and the number of scar therapies available, none are highly effective at preventing HSc after burn injury. Recent Advances: Recent studies modulating the mechanical environment surrounding incisional and excisional wounds have shown off-loading of tension to be a powerful strategy to prevent scar formation. Preclinical studies applying force perpendicular to the surface of the skin or using a combination of pressure both circumferentially and perpendicularly have shown substantial reductions in scar thickness and contraction after burn injury. Critical Issues: Though pressure therapy is highly effective in preclinical studies, outcomes in clinical studies have been variable and may be a result of differing therapy protocols and garment material fatigue. A recent adult clinical study reported a significant reduction in pressure after 1 month of use and significant reduction between 1 and 2 months of use, resulting in below therapeutic doses of pressure applied after only 1 month of use. Future Directions: To enhance efficacy of pressure garments, new low-fatigue materials must be developed for use in standard garments or garments must be redesigned to allow for adjustment to compensate for the loss of pressure with time. Additionally, measurements of applied pressure should be performed routinely during clinic visits to ensure that therapeutic doses of pressure are being delivered.
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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 | 0.000 |
| 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 | 0.001 |
| 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".