What Is “Best Achievable” Practice in Implementing the Enhanced Protein‐Energy Provision via the Enteral Route Feeding Protocol in Intensive Care Units in the United States? Results of a Multicenter, Quality Improvement Collaborative
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to determine what was "best achievable practice" with the implementation of a novel enteral feeding protocol (Enhanced Protein-Energy Provision via the Enteral Route Feeding Protocol [PEP uP protocol]). METHODS: This study was a multicenter quality improvement collaborative wherein we describe nutrition practices and outcomes within PEP uP sites. We report the minimum, average, and maximal site-level performance on aspects related to nutrition practices and outcomes. RESULTS: In 2014, 7 intensive care units (ICUs) in the United States implemented the PEP uP protocol. On average, over the first 5 ICU days, patients received 35% (site range, 26%-53%) of their prescribed energy requirements and 42% (site range, 29%-66%) of their prescribed protein requirements from enteral nutrition. In PEP uP sites, 71% (site range, 58%-95%) of patients received a semidigested formula within 72 hours of admission to the ICU, 72% had a volume-based goal as the initial feeding strategy (site range, 47%-100%), 56% had prophylactic protein supplements (site range, 0%-100%), and 19% received prophylactic motility agents (site range, 0%-85%). CONCLUSIONS: There was variable success with the implementation of the different components of the PEP uP protocol. Improving the implementation of the various components may further increase nutrition delivery.
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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 | 0.158 | 0.289 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".