Body Composition in Very Preterm Infants: Role of Neonatal Characteristics and Nutrition in Achieving Growth Similar to Term Infants
Bibliographic record
Abstract
BACKGROUND: The identification of factors involved in the postnatal growth of preterm infants will help achieve growth similar to that of term infants. OBJECTIVES: As per protocol: to compare body composition in very preterm infants at term-corrected age (TCA) with that in term infants, and to explore relationships between neonatal characteristics and body composition in preterm infants. METHODS: Anthropometry, nutritional characteristics, and neonatal outcomes were prospectively collected in 26 preterm (<29 weeks) and 33 term (37-40 weeks) infants. Body composition using dual-energy X-ray absorptiometry (DXA) was measured at TCA in preterm infants and between days 7 and 10 in term infants. RESULTS: Parenteral nutrition in preterm infants provided a mean of 2.9 ± 0.2 and 2.1 ± 0.5 g/kg/day of intravenous amino acids and lipids, respectively, during the first week of life. The mean weight gain velocity from birth to DXA assessment was 12.1 ± 1.4 g/kg/day. Compared with term infants, preterm infants at TCA were shorter and lighter, with a smaller head circumference, a lower weight estimated by DXA (2,960 ± 552 vs. 3,843 ± 377 g), and increased skinfold thicknesses. Fat mass percent (13.9 ± 5.4%) and lean mass percent (84.7 ± 5.6%) in preterm infants were similar to those in term infants (14.7 ± 3.5 and 83.5 ± 3.6%, respectively). Neonatal weight gain velocity in preterm infants was positively associated with lean mass (grams). CONCLUSION: Subcutaneous fat is increased in preterm infants. Higher protein intake in preterm infants might increase weight gain velocity and achieve a lean mass comparable to that of term infants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 teacher head, 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".