Individualized target fortification of breast milk with protein, carbohydrates, and fat for preterm infants: A double-blind randomized controlled trial
Bibliographic record
Abstract
BACKGROUND & AIMS: In preterm infants, natural variation of breast milk composition makes it difficult to achieve recommended macronutrient intakes with standard fortification. Evidence suggests that nutritional deficiency induces poor postnatal growth. This study investigates impacts of target fortification on preterm growth and metabolism by adjusting breast milk macronutrients. METHODS: This study was conducted as a single-centre, double-blind, randomized controlled trial for infants <30 gestational weeks. The control group received standard fortification and the intervention group received standard plus target fortification adding modular protein, lipids, and carbohydrates. Breast milk content was measured 3x/week using a validated near-infrared bedside spectrometer (NIRS). Modulars were added to achieve recommended values. To assess total nutrient intake, all 2810 native breast milk samples were analyzed - protein and fat using bedside-NIRS, lactose using tandem mass spectrometry (UPLC-MS/MS). Body composition was measured using air displacement plethysmography. Primary outcome was weight gain during the first 21 days of intervention. RESULTS: Baseline characteristics, morbidities, and total fluid intake were not different between groups (intervention n = 52, control n = 51). The intervention group infants had higher macronutrient intakes, weight gain (21.2 ± 2.5 vs 19.3 ± 2.4 g/kg/d, mean difference: 1.9 g/kg/d, 95% CI: 0.9 - 2.9), and body weight. Infants in the intervention group from mothers with below-average breast milk protein content showed greatest impact on weight at 36 weeks (2580 ± 280 g vs 2210 ± 300 g), length, head circumference, fat, and fat-free mass. Also, feeding intolerance was less frequent, blood urea was higher, and triglycerides were lower. CONCLUSIONS: This study provides evidence that target fortification of breast milk with low macronutrient content enhances the quality of nutrition and growth and is feasible in clinical routine.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".