Exploring the development of a home nasogastric feeding program to facilitate early discharge of infants from the neonatal intensive care unit
Bibliographic record
Abstract
Achieving full oral feeding and appropriate growth are essential for discharge to home with preterm infants; however, attaining these goals can prolong discharge timing, increase resource utilization, and impose significant stress on families. Although some NICUs around the world have demonstrated success in home nasogastric (NG) feeding programs, these programs are absent in Canada due to the lack of specialized nutritional and feeding support in neonatal follow-up clinics. Within Windsor Regional Hospital (WRH), the neonatal unit offers post-discharge nutritional support through in-house dietitians which makes implementing a home NG feeding program in Windsor-Essex possible. Before implementing this program locally, it is essential to understand the short and long-term impacts on families, thus, we plan to review the readmission rates and emergency room visits of infants discharged with a nasogastric tube from WRH between January 2015 and December 2021. This study will also assess discharge timing and nasogastric feeding duration and its impact on infant growth and family’s quality of life. This research will provide insights into the feasibility of implementing a home NG feeding program in Windsor-Essex, leading to potential reduced readmissions and decreased utilization of hospital resources, while also enhancing the care for infants and their families.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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".