Clinical Experience With Numeta in Preterm Infants
Bibliographic record
Abstract
BACKGROUND: A new "ready-to-use" triple-chamber container, Numeta (Baxter, Deerfield, IL), is available for preterm parenteral nutrition (PN) to provide nutrients according to the recommendations of the European Society for Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) and the European Society for Clinical Nutrition and Metabolism (ESPEN) Guidelines for Pediatric Parenteral Nutrition. We investigated the clinical application of Numeta compared with individualized PN in preterm infants (≤1.500 g) and evaluated the effects on nutrient intake, costs, and preparation time. MATERIALS AND METHODS: In a clinical observational study, prescriptions for preterm infants were performed with the new prescription software catoPAN (Cato Software Solutions, Becton Dickinson, Vienna, Austria). Individualized PN and Numeta prescriptions were mirrored, and nutrition content of the PNs was compared with each other and with ESPGHAN/ESPEN recommendations. Furthermore, costs and preparation time were assessed. RESULTS: In total, 374 PN solutions (>1000 g [n = 333]/≤1000 g [n = 41]) were analyzed. Protein intake with Numeta was significantly lower compared with individualized PN and did not meet the recommendations for infants <1500 g during the first day and the period of transition after birth. Energy intake was significantly higher with Numeta. The costs for Numeta preparations were €18 (about US$20) higher than for individualized PN. However, the preparation time/solution was 2 minutes faster with Numeta. CONCLUSION: Numeta is an alternative to individualized PN for infants >1000 g in the period of stable growth when enteral feedings have already started. Protein intake is significantly lower than in individualized PN solutions. Numeta is more expensive in comparison to individualized PN but saves human resources.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".