Surgical Escharotomy and Decompressive Therapies in Burns
Bibliographic record
Abstract
Early recognition of the need for escharotomy and other decompressive therapies is imperative for experienced burn providers, as to avoid reversible tissue ischemia and necrosis. With full-thickness burns, the eschar that develops is largely noncompliant. The predictable edema that develops during resuscitation of larger burns increases the likelihood ischemia-inducing pressure, as the underlying tissues swell within noncompliant skin, resulting in burn-induced compartment syndrome. Conventionally, this has been treated with decompressive therapies, such as escharotomy. The most recent surveys have identified that the United States and Canada both face a shortage of practicing burn surgeons. In the event of a burn disaster, many nonburn surgeons would need to provide burn care, including decompressive therapies. We reviewed the literature to provide accurate, accessible, and applicable recommendations regarding this practice following burn injury for both the practicing burn surgeon and those that would provide care in the burn disaster.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".