Meeting nutritional targets of critically ill patients by combined enteral and parenteral nutrition: review and rationale for the EFFORTcombo trial
Bibliographic record
Abstract
While medical nutrition therapy is an essential part of the care for critically ill patients, uncertainty exists about the right form, dosage, timing and route in relation to the phases of critical illness. As enteral nutrition (EN) is often withheld or interrupted during the intensive care unit (ICU) stay, combined EN and parenteral nutrition (PN) may represent an effective and safe option to achieve energy and protein goals as recommended by international guidelines. We hypothesise that critically ill patients at high nutritional risk may benefit from such a combined approach during their stay on the ICU. Therefore, we aim to test if an early combination of EN and high-protein PN (EN+PN) is effective in reaching energy and protein goals in patients at high nutritional risk, while avoiding overfeeding. This approach will be tested in the here-presented EFFORTcombo trial. Nutritionally high-risk ICU patients will be randomised to either high (≥2·2 g/kg per d) or low protein (≤1·2 g/kg per d). In the high protein group, the patients will receive EN+PN; in the low protein group, patients will be given EN alone. EN will be started in accordance with international guidelines in both groups. Efforts will be made to reach nutrition goals within 48-96 h. The efficacy of the proposed nutritional strategy will be tested as an innovative approach by functional outcomes at ICU and hospital discharge, as well as at a 6-month follow-up.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".