Effect of Parenteral Nutrition-Associated Factors on the Growth of Premature Infants
Bibliographic record
Abstract
Objective: To investigate the factors that affect the growth of preterm infants who receive parenteral nutrition (PN).Methods: A retrospective cohort study was performed in Uttaradit hospital, Thailand, using data collected between January 2012 and July 2016. The main outcome measure was postnatal growth failure (PGF), comprising weight gain rate at 36 weeks, weight at 36 weeks, time to regain birth weight and growth failure at 36 weeks.Results: Eighty preterm infants were included in this study, with a mean gestational age of 32 weeks and birth weight of 1468 grams. Multiple regression analysis indicated that the time to achieve full enteral feeding (r = 0.33, 95% CI[0.01,0.48]) was associated with the weight gain rate at 36 weeks of corrected age, birth weight (r = -0.53, 95% CI[-445.04, -216.70]) was associated with weight at 36 weeks of corrected age, the initial timing of PN (r = -0.24, 95% CI[-4.10, -0.40]), average amount of protein in PN (r = 0.39, 95% CI[0.55, 3.43]) and the initial amount of protein in PN (r = -0.46, 95% CI[-3.19, -1.00]) were associated with the time to regain birth weight, and a birth weight classified as small for gestational age (SGA, OR = 15.90, 95% CI[1.54,164.14]) was significantly associated with growth failure at 36 weeks of corrected age.Conclusions: The results of this study indicate that both nutrition and non-nutrition factors affect PGF in preterm infants who receive PN.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".