Standard formulas and individualised parenteral nutrition preparations in very low birth weight infants
Bibliographic record
Abstract
Background/objectives: Optimal nutrition in very low birth weight (VLBW) infants is associated with improved clinical outcomes. When parenteral nutrition (PN) with a marketing authorisation is not appropriate, hospital pharmacies can prepare more suitable PN preparation. This corresponds to standard preparations (i.e., available at any time with a fixed composition) or individualised ones (i.e., available after a period of prescription, preparation, and pharmaceutical control). In France, 12 standard formulas to be compounded were proposed by a national consortium in 2018. The objective of the present study was to evaluate whether individualised PN preparations ordered in our hospital are substitutable by one of the 12 standard formulas. Methods: All PN prescriptions for VLBW infants made in 2021 in our hospital were retrospectively extracted. For each prescription, the theoretical intakes that an infant would have received if a standard preparation had been administered were calculated. Standard and individualised preparations were compared using the Mann-Whitney U test for each component. Secondly, the relative difference between the expected intakes and effectively intakes was calculated for each component. Results/Discussion: Over the study period, 1708 prescriptions were identified (corresponding to 1708 PN individualised preparations). Most infants were extremely low birth weight infants. Based on the methods of comparison, none of the 12 standard formulas fitted with targeted intakes achieved with individualised PN preparations ordered, whereas prescriptions did fit with international guidelines. Conclusion: The study highlights how it is difficult to establish nationally standard PN formulas for VLBW infants; the development of local standard formulas seems therefore relevant.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".