Feeding critically ill patients: What is the optimal amount of energy?
Bibliographic record
Abstract
Hypermetabolism and malnourishment are common in the intensive care unit. Malnutrition is associated with increased morbidity and mortality, and most intensive care unit patients receive specialized nutrition therapy to attenuate the effects of malnourishment. However, the optimal amount of energy to deliver is unknown, with some studies suggesting that full calorie feeding improves clinical outcomes but other studies concluding that caloric intake may not be important in determining outcome. In this narrative review, we discuss the studies of critically ill patients that examine the relationship between dose of nutrition and clinically important outcomes. Observational studies suggest that achieving targeted caloric intake might not be necessary since provision of approximately 25% to 66% of goal calories may be sufficient. Randomized controlled trials comparing early aggressive use of enteral nutrition compared with delayed, less aggressive use of enteral nutrition suggest that providing increased calories with early, aggressive enteral nutrition is associated with improved clinical outcomes. However, energy provision with parenteral nutrition, either instead of or supplemental to enteral nutrition, does not offer additional benefits. In summary, the optimal amount of calories to provide critically ill patients is unclear given the limitations of the existing data. However, evidence suggests that improving adequacy of enteral nutrition by moving intake closer to goal calories might be associated with a clinical benefit. There is no role for supplemental parenteral nutrition to increase caloric delivery in the early phase of critical illness. Further high-quality evidence from randomized trials investigating the optimal amount of energy intake in intensive care unit patients is needed.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.001 |
| 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".