PP473 Topic: AS18–Nutrition Support/Fluids: DOES VOLUME-BASED ENTERAL FEEDING IMPROVE NUTRIENT DELIVERY IN HOSPITALIZED CRITICALLY ILL CHILDREN? PROTOCOL FOR A RANDOMIZED FEASIBILITY TRIAL OF VOLUME VERSUS RATE-BASED ENTERAL NUTRITION
Bibliographic record
Abstract
Aims & Objectives: Early optimal enteral nutrition (EN) is associated with better clinical outcomes, including mortality, in critically ill children. Frequent feed interruptions are common resulting in underfeeding and nutrient deficits. Traditionally tube feedings are provided using hourly rate-based feeding, which directs the nurse to run feeds at the prescribed hourly rate. Volume-based feeding allows bedside nurses to adjust feed rates to compensate for disruptions. Funding: ASPEN Rhodes Research Foundation Objectives: Determine the feasibility of a randomized control trial (RCT) to evaluate Volume-based EN by: Determine RCT participant enrollment and recruitment rates. Measure adherence to the study protocol. Determine the consent rate under a deferred consent strategy. Describe caregiver and patient perceptions and experiences around deferred consent. Methods: We will conduct a single-center parallel partially blinded 1:1 randomized feasibility trial of 56 children admitted to the ACH PICU comparing Volume-based EN (intervention) versus Rate-based EN (control). Children 1-month to 18 years of age, anticipated PICU admissions ≥ 48 hours and to be initiated on EN support will be eligible. Volume-based EN: Bedside nurses receive a daily feed volume to administer over a 24-hour period. After feeds are held, rates will be adjusted to meet this goal. Rate-based EN (usual care): Bedside nurses receive an hourly feed rate to administer over a 24-hour period. Nurses will not adjust feeds to compensate for interruptions. Results: Recruitment anticipated to commence in March 2024. Conclusions: This feasibility trial will inform a full-scale RCT assessing the impact of volume-based EN on nutritional intakes and hospital outcomes for critically ill children. Keywords: Nutrition, Randomized Controlled Trial, RCT
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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 | 0.027 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.104 | 0.017 |
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".