Metabolic support in the critically ill: a consensus of 19
Bibliographic record
Abstract
Metabolic alterations in the critically ill have been studied for more than a century, but the heterogeneity of the critically ill patient population, the varying duration and severity of the acute phase of illness, and the many confounding factors have hindered progress in the field. These factors may explain why management of metabolic alterations and related conditions in critically ill patients has for many years been guided by recommendations based essentially on expert opinion. Over the last decade, a number of randomized controlled trials have been conducted, providing us with important population-level evidence that refutes several longstanding paradigms. However, between-patient variation means there is still substantial uncertainty when translating population-level evidence to individuals. A cornerstone of metabolic care is nutrition, for which there is a multifold of published guidelines that agree on many issues but disagree on others. Using a series of nine questions, we provide a review of the latest data in this field and a background to promote efforts to address the need for international consistency in recommendations related to the metabolic care of the critically ill patient. Our purpose is not to replace existing guidelines, but to comment on differences and add perspective.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".