Factors affecting continuation of mother’s-own-(breast)milk feeding until discharge from the NICU for infants born preterm less than 32 weeks: A cohort study
Bibliographic record
Abstract
Abstract Objectives To quantify the feeding volumes and factors associated with feeding mothers-own-(breast) milk until discharge for preterm neonates born less than 32 weeks. Methods This was a retrospective cohort study (2010-2020). Neonates born <32 weeks and admitted to NICU with stored feeding records were eligible for inclusion. Information about daily feeding patterns (volume and sources), maternal demographics, birth data, and postnatal conditions were abstracted using standard data collection forms. Descriptive and inferential statistics were used to analyze results and compare groups. Results Of 436 newborns born <32 weeks, 372 met the inclusion criteria for the final analysis. While 87.9% of neonates had fed with mother’s-own-milk initiated, only 53.5% continued these feeds until discharge from NICU. Over the study period, there was a significant decline in both initiation (P = 0.002) and continuation of feeds with mother’s-own-milk (P < 0.0001). Factors positively associated with the continuation of mother’s-own-milk to hospital discharge included older maternal age (P = 0.0002) and primiparity (P = 0.002). Continuation of mother’s-own-milk was also associated with an earlier date of first feed with mother’s-own-milk and higher volumes of breast milk production (P < 0.004). Volume of mother’s-own-milk fed on Day 7 of admission was significant in predicting continuation to discharge. Factors negatively associated with continuation of feeds to discharge included high BMI (P = 0.009), cigarette smoking (P = 0.004), substance abuse (P = 0.0001), multiples (P = 0.038), and remote residence (P = 0.002). Conclusions Early initiation of mother’s-own-(breast)milk improves continuation throughout NICU admission until discharge. Investigation into barriers to breastfeeding and targeted support for mothers (particularly those that are younger, multiparous, and/or from remote locations) are urgently needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".