The Effect of Individualized Versus Standardized Parenteral Nutrition on Body Weight in Very Preterm Infants
Bibliographic record
Abstract
BACKGROUND: This study was designed to evaluate whether standardizing total parenteral nutrition (TPN) is at least non-inferior to TPN with individualized composition in premature infants with a gestational age (GA) < 32 weeks. METHODS: In this retrospective cohort study, all preterm born in or transferred to Maxima Medical Center (MMC) within 24 hours after birth with a GA < 32 weeks were included. The individualized group (2011) was compared to the partially standardized group (2012) and completely standardized group (2014) consequently. The primary endpoint was difference in growth. Secondary endpoints included differences in electrolyte concentrations. RESULTS: A total of 299 preterm were included in this study. When comparing weight gain, the infants in the (partially) standardized group demonstrated significantly (P < 0.05) less weight loss during the first days of life and grew faster subsequently in the following days than the individualized TPN regimen. Furthermore, significant differences in abnormal serum sodium, chloride, calcium, creatinine, magnesium and triglycerides values were demonstrated. CONCLUSION: TPN with a (partially) standardized composition revealed to be at least non-inferior to TPN with an individualized composition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".