Calcium and phosphorus supplementation of human milk for preterm infants
Bibliographic record
Abstract
BACKGROUND: Preterm infants are born with low skeletal stores of calcium and phosphorus. Preterm human milk provides insufficient calcium and phosphorus to meet their estimated needs. OBJECTIVES: To determine if addition of calcium and phosphorus supplements to human milk leads to improved growth and bone metabolism without significant adverse effects in preterm infants. SEARCH STRATEGY: The standard search strategy of the Cochrane Neonatal Review Group (NRG) was used. This includes searches of the Oxford Database of Perinatal Trials, MEDLINE, previous reviews including cross references, abstracts, conferences and symposia proceedings, expert informants, journal handsearching mainly in the English language. SELECTION CRITERIA: All trials utilizing random or quasi-random allocation to supplementation of human milk with calcium and/or phosphorus or no supplementation in preterm infants within a hospital were eligible. DATA COLLECTION AND ANALYSIS: Data were extracted using the standard methods of the Cochrane NRG, with separate evaluation of trial quality and data extraction by each author and synthesis of data using relative risk and weighted mean difference. MAIN RESULTS: No studies which met selection criteria were identified. Excluded studies that were identified included minerals as one component of a multicomponent fortifier or reported only non-clinical outcomes (for example, urinary excretion of calcium). Two studies were excluded because of methodological concerns. REVIEWER'S CONCLUSIONS: There are no randomized controlled data evaluating clinical outcomes of calcium and phosphorus supplementation of human milk for preterm infants on which to base practice recommendations. Further trials should assess the clinical benefits and potential adverse effects of supplementation of human milk with minerals. This may best be done in the context of manipulation of the composition of human milk fortifiers containing multiple nutrients (carbohydrate, protein, and minerals).
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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 | 0.014 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| 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".