A national survey of the enteral feeding practices in Canadian neonatal intensive care units
Bibliographic record
Abstract
AIM: Nutrition affects the growth and neurodevelopmental outcomes of preterm infants, yet controversies exist about the optimal enteral feeding regime. The objective of this study was to compare enteral feeding guidelines in Canadian neonatal intensive care units (NICUs). METHOD: The research team identified key enteral feeding practices of interest. Canadian Neonatal Network site investigators at 30 Level 3 NICUs were contacted to obtain a copy of their 2016 to 2017 feeding guidelines for infants who weighed less than 1,500 g at birth. Each guideline was reviewed to compare recommendations around the selected feeding practices. RESULTS: Five of the 30 NICUs did not have a feeding guideline. The other 25 NICUs used 22 different enteral feeding guidelines. The guidelines in 40% of those NICUs recommend commencing minimal enteral nutrition (MEN) within 24 hours of birth and maintaining that same feeding volume for 24 to 96 hours. In 40% of NICUs, the guideline recommended that MEN be initiated at a volume of 5 to 10 mL/kg/day for infants born at <1,000 g. Guidelines in all 25 NICUs recommend the use of bovine-based human milk fortifier (HMF), and in 56% of NICUs, it is recommended that HMF be initiated at a total fluid intake of 100 mL/kg/day. Guidelines in only 16% of NICUs recommended routine gastric residual checks. Donor milk and probiotics are used in 76% and 72% of the 25 NICUs, respectively. CONCLUSION: This study revealed substantial variability in recommended feeding practices for very low birth weight infants, underscoring the need to establish a national feeding guideline for this vulnerable group.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".