Outcome comparison of very preterm infants cared for in the neonatal intensive care units in <scp>A</scp>ustralia and <scp>N</scp>ew <scp>Z</scp>ealand and in <scp>C</scp>anada
Bibliographic record
Abstract
AIM: To compare risk-adjusted neonatal intensive care unit outcomes between regions of similar population demography and health-care systems in Australia-New Zealand and Canada to generate meaningful hypothesis for outcome improvements. METHODS: Retrospective study of data from preterm infants (<32 weeks gestational age) cared for in 29 ANZNN (Australian and New Zealand Neonatal Network) and 26 Canadian Neonatal Network (CNN) intensive care unit admitted between 2005 and 2007. Moribund infants or those with major congenital malformation were excluded. RESULTS: The 9995 ANZNN infants had a higher gestational age (29 vs. 28 weeks, P < 0.0001), lower rate of outborn status (13.2% vs. 19.1%, P < 0.0001) and Apgar score <7 at 5 min (14.8% vs. 21.6%, P < 0.0001) than their 7141 CNN counterparts. After adjustment, ANZNN and CNN infants had a similar likelihood of survival (adjusted odds ratio (AOR) 1.01 (0.88, 1.16)), but ANZNN infants were at lower risk of severe retinopathy (AOR 0.71 (0.61, 0.83)), severe ultrasound neurological injury (AOR 0.68 (0.59, 0.78)), necrotising enterocolitis (AOR 0.65 (0.56, 0.76)), chronic lung disease (AOR 0.67 (0.62, 0.73)) and late-onset sepsis (AOR 0.83 (0.76, 0.91)). ANZNN infants were at a higher risk of pulmonary air leak (AOR 1.20 (1.01, 1.42)), early-onset sepsis (AOR 1.33 (1.02, 1.74)). More ANZNN infants received any respiratory support (AOR 1.27 (1.14, 1.41)) and continuous positive airway pressure as sole respiratory support (AOR 2.50 (2.27, 2.70)). CONCLUSIONS: Despite similarities in settings, ANZNN infants fared better in most measures. Outcome disparities may be related to differences in tertiary service provision, referral and clinical practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".