Bibliographic record
Abstract
The effect of nutritional support in critically ill patients with sepsis has received much attention in recent years. However, many of the studies have produced conflicting results. As for all critically ill patients, nutritional support, preferably via the enteral route, should be commenced once initial resuscitation and adequate perfusion pressure is achieved. Where enteral feeding is impossible or not tolerated, parenteral nutrition (either as total or complimentary therapy) may safely be administered. Most positive studies relating to nutritional support and sepsis have been in the setting of sepsis prevention. Thus, the administration of standard nutrition formulas to critically ill patients within 24 h of injury or intensive care unit admission may decrease the incidence of pneumonia. Both arginine-supplemented enteral diets, given in the perioperative period, and glutamine-supplemented parenteral nutrition have been shown to decrease infections in surgical patients. Parenteral fish oil lipid emulsions as well as probiotics given in the perioperative period may also reduce infections in patients undergoing major abdominal operations, such as liver transplantation. There is little support at the present time for the positive effect of specific pharmaconutrients, in particular fish oil, probiotics, or antioxidants, in the setting of established sepsis. More studies are clearly required on larger numbers of more homogeneous groups of patients.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".