Enhanced Protein-Energy Provision via the Enteral Route Feeding (PEPuP) Protocol in Critically Ill Surgical Patients: A Multicentre Prospective Evaluation
Bibliographic record
Abstract
Suboptimal levels of feeding in critically ill patients are associated with poor clinical outcomes. The Enhanced Protein-Energy Provision via the Enteral Route Feeding (PEPuP) protocol was developed to improve nutritional delivery in the critically ill and has been studied in several hospitals. However, the experience with this protocol in surgical patients is limited to date. The objective of this analysis was to describe the experience with this protocol in surgical patients. We analysed observational patient data obtained from the 2013 International Nutrition Survey. We compared nutritional practices and outcomes of patients admitted for surgical and medical reasons to ICUs in sites that implemented the PEPuP protocol. We used surgical ICU patients in non-PEPuP sites as a concurrent control group. In sites that implemented the PEPuP protocol, surgical patients received a smaller proportion of prescribed calories (43% versus 61%, P=0.004) and protein (38% versus 57%, P=0.002) compared to medical patients. When compared to the cohort of surgical patients from control sites, the surgical patients from PEPuP sites received similar amounts of calories and protein. Although surgical PEPuP patients were more likely to receive trophic and volume-based feeds compared to surgical patients in control sites, other aspects of the PEPuP protocol were not adequately implemented. We conclude that nutritional delivery to surgical patients remains inadequate and the PEPuP protocol seems ineffective in improving nutritional intake in this population. Further research to determine methods of optimising PEPuP protocol implementation and adherence in surgery 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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".