Postdischarge Feeding of Very‐low‐birth‐weight Infants
Bibliographic record
Abstract
OBJECTIVES: Infant feeding guidelines are important public health strategies to promote optimal growth, development, and chronic disease prevention, but their effectiveness is contingent upon families' ability to adhere to them. Little is known of adherence to guidelines among nutritionally vulnerable infants, specifically those born very-low-birth-weight (VLBW) (<1500 g). This study investigated whether postdischarge feeding practices for VLBW infants align with current recommendations and explored parental and infant baseline sociodemographics related to these practices. METHODS: Prospectively collected data from families of 300 VLBW infants participating in a randomized clinical trial (ISRCTN35317141) were used. Baseline demographics were obtained at enrollment and postdischarge feeding practices via monthly telephone questionnaires to 6 months corrected age (CA). RESULTS: At discharge, 4 and 6 months CA, 72%, 39%, and 29% of infants received any amount of mother's milk, respectively; exclusive breast-feeding rates were 49%, 20%, and 6%, respectively. Among infants receiving mother's milk, rates of vitamin D supplementation were ≥83%. Recommendations for introducing solids between 4 and 6 months CA were followed by 71% of the cohort and for iron supplementation by 58%. Overall, 12% of infants adhered to all aforementioned recommendations. Mothers with university degrees were more likely to provide mother's milk, whereas mothers of Middle Eastern/South Asian ethnicity were less likely to provide mother's milk. CONCLUSIONS: Low rates of partial and exclusive breast-feeding of VLBW infants to 6 months CA were reported. Overall adherence to iron supplementation was low. Strategies to provide increased support for mothers identified as at-risk should be developed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".