Nutrition and infection in the intensive care unit: what does the evidence show?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Nutrition support when applied appropriately, can improve clinical outcomes, particularly the incidence of infections. The Canadian Clinical Practice Guidelines for Nutrition Support, published in October 2003, summarized the evidence on nutrition support in the critically ill patient and provided recommendations aimed at maximizing the benefits of nutrition support while minimizing the risks. The purpose of this review is to highlight recent advances in nutrition research in critically ill adult patients, particularly with respect to minimizing infection. The newly published data will be used to update the Canadian Clinical Practice Guidelines. RECENT FINDINGS: Recent studies have confirmed that the use of enteral nutrition versus parenteral nutrition, early initiation of enteral nutrition, use of enteral and parenteral glutamine and intensive insulin therapy are all associated with reduced infectious morbidity in critically ill patients. A recent meta-analysis suggests that antioxidant supplementation is associated with no improvement in infectious complications, but an increase in survival. The recommendations from the Canadian Clinical Practice Guidelines for Nutrition Support have been updated based on the data from these recent trials. SUMMARY: This review provides insights into the results of recent randomized trials on nutrition support in critically ill patients. The Canadian Clinical Practice Guidelines for nutrition support help intensive care unit clinicians to keep abreast of emerging evidence and the impact of nutrition support practices on outcomes such as infections.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".