Nutrition in Burns
Bibliographic record
Abstract
Aggressive nutrition support is recommended following severe burn injury. Initially, such injury results in a prolonged and persistent hypermetabolic response mediated by a 10- to 20-fold elevation in plasma catecholamines, cortisol, and inflammatory mediators. This response leads to twice-normal metabolic rates, whole-body catabolism, muscle wasting, and severe cachexia. Thus, it is relevant to review the literature on nutrition in burns to adjust/update treatment. Failure to meet the increased substrate requirements may result in impaired wound healing, multiorgan dysfunction, increased susceptibility to infection, and death. Therefore, aggressive nutrition support is essential to ensure adequate burn care, attenuate the hypermetabolic response, optimize wound healing, minimize devastating catabolism, and reduce morbidity and mortality. Here, the authors provide nutrition recommendations gained from prospective trials, retrospective analyses, and expert opinions based on the authors' practices in Galveston, Texas, and Vienna, Austria.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".