Assessing the Metabolic and Clinical Consequences of Early Enteral Feeding in the Malnourished Patient
Bibliographic record
Abstract
BACKGROUND: It is often thought that enteral feeding should be initiated slowly in those who are severely malnourished. This descriptive study examined the effect of an enteral feeding protocol on the typical metabolic consequences seen in refeeding syndrome. METHODS: A retrospective chart review was conducted on 51 patients who had been placed on hospital-wide enteral feeding and electrolyte replacement protocols over a 9-month period to determine whether there were any negative clinical consequences to early feeding. RESULTS: Goal feeding rate was achieved within 17.6 +/- 8.7 hours. Forty patients (80%) developed depletions in phosphate, magnesium, or potassium after initiation of enteral feeding, including 93% of those deemed "at risk" and 74% of those "not at risk." All patients received electrolyte replacement according to protocols, and no patients showed any negative clinical effect. CONCLUSIONS: This study showed that malnourished patients at risk for refeeding syndrome can be fed early without observed negative clinical consequences. An electrolyte replacement protocol may be an effective means of minimizing the electrolyte imbalances associated with early feeding. It also demonstrated the significance of applying such protocols to all patients requiring enteral support, as current methods of assessing "risk"for refeeding syndrome may be inadequate.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".