Association of Caloric Intake, Protein Intake, and Enteral Feeding Initiation with Weight Gain in Infants Born 32 to 34 Weeks' Gestation
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the association of caloric intake, protein intake, and enteral feed initiation time in the first 3 days of life with weight loss percentage (%WL) at 7 days among infants born 32 to 34 weeks' gestational age (GA). STUDY DESIGN: This is a retrospective cohort study of 252 infants admitted to a neonatal intensive care unit. Patient data included patient characteristics, daily weight, intake, and method of nutrition in the first 3 days. Multivariate linear regression was used to explore associations between outcome (%WL at day 7 of life) and exposures (caloric intake, protein intake, and enteral feed initiation time) and adjusted for covariates (GA, birth weight, and sex). RESULTS: Median 7 days %WL was 2.3% (interquartile range: -5.2, 1.2). Average caloric intake and average protein intake in the first 3 days were 57 kcal/kg/d and 2.3 g/kg/d. In the adjusted linear regression, caloric intake and protein intake (coefficient = 0.03, 95% confidence interval [CI]: -0.06, 0.09 and coefficient = 0.11, 95% CI: -0.36, 2.30) were not associated with %WL at 7 days. Enteral feeds ≤12 hours were associated with less %WL at 7 days of life (Coef = -0.15, 95% CI: -2.67, -0.17). CONCLUSION: Enteral feeds ≤12 hours after delivery is associated with lower %WL at 7 days among preterm infants 32 to 34 weeks' GA.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".