Supporting Direct Breastfeeding for a Tracheostomy-Dependent Extremely Premature Infant: A Case Study
Bibliographic record
Abstract
INTRODUCTION: The benefits of human milk for preterm infants are well documented. Complex medical conditions can limit the extremely premature infant's ability to breastfeed and to receive human milk directly, yet these vulnerable infants may benefit most from receiving it. MAIN ISSUE: Extremely preterm infants are at risk for infections, digestive challenges, and chronic lung disease, and occasionally require a tracheostomy to facilitate weaning from mechanical ventilation. There is a risk of aspiration when orally feeding a child with a tracheostomy. This case study describes a tertiary neonatal team supporting a family's direct breastfeeding goal in an extremely premature infant with a diagnosis of bronchopulmonary dysplasia requiring a tracheostomy. MANAGEMENT: Initially, the infant participant (born at 24 weeks and 3 days of gestation, with a birthweight of 540 g) was gavage fed with human milk. The interdisciplinary team collaborated with the family to guide the infant's feeding goals, providing positive oral stimulation with soothers, oral immune therapy, and frequent skin-to-skin contact to prepare for future oral feeding. Within a month of the tracheotomy procedure, oral feeding was initiated, and direct breastfeeding with the tracheostomy tubing in place was achieved at 50 weeks and 1 day of age as a primary source of nutrition. CONCLUSION: The open dialogue between the family and healthcare team was the foundation for trialing direct breastfeeding for an extremely premature infant with a tracheostomy. While direct breastfeeding of full-term infants with tracheostomies has been previously described in the literature, this is the first case study of an extremely premature infant with a tracheostomy transitioning to direct breastfeeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| 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".