Anabolic and anticatabolic agents in critical care
Bibliographic record
Abstract
PURPOSE OF REVIEW: A complex network of hormones and other effectors characterize the hypermetabolic response in critical illness; these mediators work together to induce numerous pathophysiologic alterations. Increased incidence of infection, multiorgan failure, long-term debilitation, delays in rehabilitation, and death result from an inability to meet the prohibitively elevated protein and energy requirements, which occur during illness and can persist for several years. Pharmacologic interventions have been successfully utilized to attenuate particular aspects of the hypermetabolic response; these modalities are a component of managing critically ill patients - including those patients with severe burns. Here, we review recent advances in pharmacologically attenuating the hypermetabolic and catabolic responses. RECENT FINDINGS: Propranolol, a nonspecific β-adrenergic receptor antagonist, is one of the most widely used anticatabolic therapies. Oxandrolone, testosterone, and intensive insulin therapy represent anabolic pharmacological strategies. Promising therapies, such as metformin, glucagon-like peptide 1, peroxisome proliferator-activated receptor agonists, are currently being investigated. SUMMARY: Profound metabolic derangements occur in critically ill patients; this hypermetabolic response is a major contributor to adverse outcomes. Despite the pharmacological therapies currently available to counteract this devastating cascade, future studies are warranted to explore new multimodality agents that will counteract these effects while maintaining glycemic control and preventing unfavorable complications.
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.
How this classification was reachedexpand
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".