Burn-induced hypermetabolism and skeletal muscle dysfunction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Critical illnesses, including sepsis, cancer cachexia, and burn injury, invoke a milieu of systemic metabolic and inflammatory derangements that ultimately results in increased energy expenditure leading to fat and lean mass catabolism. Burn injuries present a unique clinical challenge given the magnitude and duration of the hypermetabolic response compared with other forms of critical illness, which drastically increase the risk of morbidity and mortality. Skeletal muscle metabolism is particularly altered as a consequence of burn-induced hypermetabolism, as it primarily provides a main source of fuel in support of wound healing. Interestingly, muscle catabolism is sustained long after the wound has healed, indicating that additional mechanisms beyond wound healing are involved. In this review, we discuss the distinctive pathophysiological response to burn injury with a focus on skeletal muscle function and metabolism. We first examine the diverse consequences on skeletal muscle dysfunction between thermal, electrical, and chemical burns. We then provide a comprehensive overview of the known mechanisms underlying skeletal muscle dysfunction that may be attributed to hypermetabolism. Finally, we review the most promising current treatment options to mitigate muscle catabolism, and by extension improve morbidity and mortality, and end with future directions that have the potential to significantly improve patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it