Bibliographic record
Abstract
PURPOSE OF REVIEW: This paper highlights recent studies of interest and provides rationale for why deficiencies with the current scientific paradigm of immunonutrition has produced studies with conflicting results, and why it should be replaced with a new paradigm termed 'pharmaconutrition'. RECENT FINDINGS: Considering the overall treatment effect of immune-modulating nutrients, parenteral glutamine is recommended in patients receiving parenteral nutrition, while enteral glutamine should be considered in burn and trauma patients. Antioxidants, particularly selenium, should be considered for critically ill patients, and enteral formulas enriched with fish oils are recommended in patients with acute respiratory distress syndrome. Arginine-supplemented diets are not recommended. There are currently insufficient data to enable useful recommendations on the optimal route, timing, duration and dosage of each nutrient. The pending results of a large, rigorously designed, randomized trial, however, in which nutrients are viewed and tested as pharmacological agents, promise to clarify some of the current ambiguities and inform future practice. SUMMARY: This review provides insights into why the current paradigm of immunonutrition has failed to consistently demonstrate a beneficial effect of key immunomodulating nutrients, and offers a timely solution through the new paradigm of pharmaconutrition.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| 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".