Enteral Nutrition in Preterm Infants (2022)
Bibliographic record
Abstract
OBJECTIVES: To review the current literature and develop consensus conclusions and recommendations on nutrient intakes and nutritional practice in preterm infants with birthweight <1800 g. METHODS: The European Society of Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) Committee of Nutrition (CoN) led a process that included CoN members and invited experts. Invited experts with specific expertise were chosen to represent as broad a geographical spread as possible. A list of topics was developed, and individual leads were assigned to topics along with other members, who reviewed the current literature. A single face-to-face meeting was held in February 2020. Provisional conclusions and recommendations were developed between 2020 and 2021, and these were voted on electronically by all members of the working group between 2021 and 2022. Where >90% consensus was not achieved, online discussion meetings were held, along with further voting until agreement was reached. RESULTS: In general, there is a lack of strong evidence for most nutrients and topics. The summary paper is supported by additional supplementary digital content that provide a fuller explanation of the literature and relevant physiology: introduction and overview; human milk reference data; intakes of water, protein, energy, lipid, carbohydrate, electrolytes, minerals, trace elements, water soluble vitamins, and fat soluble vitamins; feeding mode including mineral enteral feeding, feed advancement, management of gastric residuals, gastric tube placement and bolus or continuous feeding; growth; breastmilk buccal colostrum, donor human milk, and risks of cytomegalovirus infection; hydrolyzed protein and osmolality; supplemental bionutrients; and use of breastmilk fortifier. CONCLUSIONS: We provide updated ESPGHAN CoN consensus-based conclusions and recommendations on nutrient intakes and nutritional management for preterm infants.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".