Effect of Docosahexaenoic Acid (DHA) Supplementation of Preterm Infants on Growth, Body Composition, and Blood Pressure at 7-Years Corrected Age: Follow-Up of a Randomized Controlled Trial
Bibliographic record
Abstract
Aim: To determine if supplementation of infants born <33 weeks’ gestation with higher dose docosahexaenoic acid (DHA) affects growth, body composition, and blood pressure at 7 y corrected age (CA) and if treatment effects differed by infant sex at birth and birth weight strata (<1250 and ≥1250 g). Methods: Seven-year follow-up of an Australian multicenter randomized controlled trial in which 657 infants were fed high-DHA (≈1% total fatty acids) enteral feeds or standard-DHA (≈0.3% total fatty acids) from age 2−4 d until term CA. Seven-year CA outcomes were growth (weight, height), body composition (lean body mass, fat mass, waist, and hip circumference), and blood pressure. Results: There was no effect of high-DHA enteral feeds compared with standard-DHA on growth, body composition, and blood pressure at 7-year CA either overall or in subgroup analysis by sex. There was a significant interaction between high-DHA and birthweight strata on height at 7-y CA (p = 0.03). However, the post-hoc analyses by birthweight strata did not reach significance (p > 0.1). High-DHA group infants were more likely to be classified as obese (relative risk 1.6 (95% CI 1.0, 2.6); p = 0.05). Conclusions: DHA supplementation of premature infants did not affect growth, body composition, or blood pressure at 7-year CA overall by sex and birthweight strata. The finding of a higher risk of obesity in children who receive high-DHA needs to be interpreted with caution due to the small number of children classified as obese.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".