A population-based comparison of preterm neonatal deaths (22–34 gestational weeks) in France and Ontario: a cohort study
Bibliographic record
Abstract
BACKGROUND: The management and outcomes of preterm births can vary greatly even among developed nations with the same access to medicine, technology and expertise. We aimed to compare aspects of obstetrical management and mortality for preterm infants in France and Ontario, Canada. METHODS: The Better Outcomes Registry & Network (BORN) Information System in Ontario and Épidémiologique sur les petits âges gestationnels (EPIPAGE-2) in France collected information on maternal demographics, obstetrical characteristics, obstetrical interventions and neonatal outcomes for infants born between 22 and 34 weeks gestation. We used standardized covariate definitions and extracted data from 2011 (for EPIPAGE-2) and from 2012 and 2013 (for BORN) to conduct a cohort study comparing the 2 data sets (stratified into gestational age groups of 22-26, 27-31 and 32-34 wk) using multivariable logistic regression models. RESULTS: Mothers in the BORN cohort were older (30.7 yr v. 29.6 yr) but less likely to have gestational hypertension (13.4% v. 17.9%) than those in the EPIPAGE-2 cohort. Infants from EPIPAGE-2 had lower birth weights (1.3 kg v. 1.5 kg) and were more likely to be born in an institution with level 3 care (71.9% v. 55.8%). After adjustment for these differences, there was significantly higher neonatal mortality among infants from EPIPAGE-2 in the 22-26 week gestation age group (adjusted odds ratio 2.81; 95% confidence interval 1.17 to 6.74). INTERPRETATION: Even after we adjusted for both intrinsic population differences and differences in management between Ontario and France, we found a higher rate of neonatal mortality at earlier gestational ages in France. This may be related to differences in ethical approaches and/or postnatal management and should be explored further.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".