Achieving Protein Targets in the ICU Using a Specialized High‐Protein Enteral Formula: A Quality Improvement Project
Bibliographic record
Abstract
BACKGROUND: To meet protein needs in critical illness (CI), guidelines suggest ≥1.2-2.5 g protein/kg/d; however, most intensive care unit (ICU) patients receive ≤0.7 g/kg/d. Higher protein enteral nutrition (EN) formulas may be part of the solution to provide prescribed protein. Our objective was to demonstrate that an EN formula with 37% protein can deliver ≥80% of prescribed protein, without overfeeding calories within the first 5 days of feeding and to describe ICU clinicians' experience. METHODS: ), nutrition targets, daily protein and energy delivered, feeding interruptions, and general tolerance were recorded. RESULTS: Forty-four of 49 patients received the formula ≥2 days. Average protein prescribed was 137.5 g/d (82.5-200) or 1.9 g/kg/d (1.5-2.5). Average protein delivered was 116.9 g/d (33.5-180) or 1.6 g/kg/d (0.4-2.4). Seventy-five percent to 83% of patients received ≥80% prescribed protein on days 2-5. Average energy prescribed was 1638.6 kcal/d (990-2500) or 17.8 kcal/kg (11-26). Average energy delivered was 1523.9 kcal/d (693.0-2557.5) or 17.3 kcal/kg/d (1.35-64.7). The formula was well tolerated with no gastrointestinal symptoms reported in 38 (86%) patients. The most common reasons to prescribe the formula were obesity and use of fat-based medications. CONCLUSIONS: We demonstrated in a QI study that a high-protein EN formula was tolerated in a small, heterogeneous group of ICU patients and effective in meeting protein targets without overfeeding.
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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 | 0.021 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".