Neonatology/Paediatrics – Guidelines on Parenteral Nutrition, Chapter 13
Bibliographic record
Abstract
There are special challenges in implementing parenteral nutrition (PN) in paediatric patients, which arises from the wide range of patients, ranging from extremely premature infants up to teenagers weighing up to and over 100 kg, and their varying substrate requirements. Age and maturity-related changes of the metabolism and fluid and nutrient requirements must be taken into consideration along with the clinical situation during which PN is applied. The indication, the procedure as well as the intake of fluid and substrates are very different to that known in PN-practice in adult patients, e.g. the fluid, nutrient and energy needs of premature infants and newborns per kg body weight are markedly higher than of older paediatric and adult patients. Premature infants <35 weeks of pregnancy and most sick term infants usually require full or partial PN. In neonates the actual amount of PN administered must be calculated (not estimated). Enteral nutrition should be gradually introduced and should replace PN as quickly as possible in order to minimise any side-effects from exposure to PN. Inadequate substrate intake in early infancy can cause long-term detrimental effects in terms of metabolic programming of the risk of illness in later life. If energy and nutrient demands in children and adolescents cannot be met through enteral nutrition, partial or total PN should be considered within 7 days or less depending on the nutritional state and clinical conditions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.015 |
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".