Narrowing the Protein Deficit Gap in Critically Ill Patients Using a Very High‐Protein Enteral Formula
Bibliographic record
Abstract
BACKGROUND: Protein deficits have been associated with longer intensive care unit (ICU) stays and increased mortality. Current view suggests if protein goals are met, meeting full energy targets may be less important and prevent deleterious effects of overfeeding. We proposed a very-high protein (VHP) enteral nutrition (EN) formula could provide adequate protein, without overfeeding energy, in the first week of critical illness. METHODS: This was a retrospective study of medical/surgical ICU patients receiving EN exclusively for ≥5 days during the first week of ICU admission. Twenty participants received standard EN; 20 participants received the VHP-EN formula (1 kcal/mL, 37% protein). Protein and energy prescribed/received, gastrointestinal tolerance, and feeding interruptions were examined. RESULTS: Forty ICU patients [average Acute Physiology and Chronic Health Evaluation II score of 20.1] were included. Protein prescribed and received was significantly higher in the VHP group vs the standard EN group (135.5 g/d ± 22.9 vs 111.4 g/d ± 25; P = .003 and 112.2 g/d ± 27.8 vs 81.7 g/d ± 16.7, respectively; P = .002). Energy prescribed and received was similar between groups (1696 kcal/d ± 402 vs 1893 kcal/d ± 341, respectively; P = .101 and 1520 kcal/d ± 346 vs 1506 ± 380 kcal/d; P = .901). There were no differences in EN tolerance (P = .065) or feeding interruptions (P = .336). CONCLUSIONS: Use of a VHP formula in ICU patients resulted in higher protein intakes without overfeeding energy or use of modular protein in the first 5 days of exclusive EN.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".