Safety of Cow's Milk-Derived Fortifiers used with an All Human Milk Base Diet in Very Low Birthweight Preterm Infants: Part II
Bibliographic record
Abstract
Recently we published a meta-analyses of morbidity seen with the use of cow’s milk derived fortifier (CMDF) rather than human milk derived fortifier (HMDF) in very low birthweight (VLBW) infants. Here, we further analyse these data to estimate the annual population risk of CMDF-related major morbidity in the United States and Canada. The outcome used was a mortality/morbidity index which was positive if the infants had one or more of death, necrotising enterocolitis, sepsis retinopathy of prematurity or broncho- pulmonary dysplasia. Using the risk difference (RD) between the CMDF and HMDF groups we estimated, provisionally, that 4150 additional VLBW infants in the United States and Canada each year, or an additional infant approximately every 2 hours, may be expected to develop a positive mortality/morbidity index in relation to being fed CMDF – over and above the number of infants with a positive index if fed HMDF. We provide an in-depth discussion of the limitations of our estimate. This analysis provides preliminary evidence of the magnitude of population risk of major neonatal morbidity with use of CMDF versus HMDF in VLBW infants in current practice.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.028 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".