Protein Kinetics and Metabolic Effects Related to Disease States in the Intensive Care Unit
Bibliographic record
Abstract
Evaluating protein kinetics in the critically ill population remains a very difficult task. Heterogeneity in the intensive care unit (ICU) population and wide spectrum of disease processes creates complexity in assessing protein kinetics. Traditionally, protein has been delivered in the context of total energy. Focus on energy delivery has recently come into question, as the importance of supplemental protein in patient outcomes has been shown in several recent trials. The ICU patient is prone to catabolism, immobilization, and impaired immunity, which is a perfect storm for massive loss of lean body tissue with a unidirectional flow of amino acids from muscle to immune tissue for immunoglobulin production, as well as liver for gluconeogenesis and acute phase protein synthesis. The understanding of protein metabolism in the ICU has been recently expanded with the discovery of how the mammalian target of rapamycin complex 1 is regulated. The concept of "anabolic resistance" and identifying the quantity of protein required to overcome this resistance is gaining support among critical care nutrition circles. It appears that a minimum of at least 1.2 g/kg/d with levels up to 2.0 g/kg/d of protein or amino acids appears safe for delivery in the ICU setting and may yield a better clinical outcome.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".