Elective transfers of preterm neonates to regional centres on non‐invasive respiratory support is cost effective and increases tertiary care bed capacity
Bibliographic record
Abstract
AIM: Managing capacity at regional facilities caring for sick neonates is increasingly challenging. This study estimated the clinical and economic impact of the elective transfer of stable infants requiring nasal continuous positive airway pressure (NCPAP) from level three to level two neonatal intensive care units (NICUs) within an established clinical network of five NICUs. METHODS: We retrospectively analysed the records of 99 stable infants transferred on NCPAP between two level three NICUs and three level two NICUs in Calgary, Canada, between June 2014 and May 2016. RESULTS: The median gestational age and weight at birth were 28 weeks and 955 g, and the median corrected gestational age and weight at transfer were 33 weeks and 1597 g, respectively. This resulted in cost savings of $2.65 million Canadian dollars during the two-year study period, and 848 level three NICU days were freed up for potentially sick neonates. There were no adverse events associated with the transfers. CONCLUSION: The elective transfer of stable neonates on NCPAP from level three to level two NICUs within an established clinical network led to substantial cost savings, was safe and increased the bed capacity at the two level three NICUs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".