Gestational age‐ and birthweight‐specific declines in infant mortality in Canada, 1985–94
Bibliographic record
Abstract
We studied infant mortality rates in Canada within specific gestational age and birthweight categories after using probabilistic techniques to link information in Statistics Canada's live births data base (1985-94) with that in the death data base (1985-95). Gestational age- and birthweight-specific mortality rates in 1992-94 were contrasted with those in 1985-87 with changes expressed in terms of relative risks with 95% confidence intervals [CI]. Statistically significant reductions in infant mortality were observed beginning at 24-25 weeks of gestation and extended across the gestational age range to post-term births. Crude infant mortality rates, infant mortality rates among those > or = 500 g and among those > or = 1000 g decreased by 22%, 25% and 26%, respectively, from 1985-87 to 1992-94. The magnitude of the reductions in infant mortality rates ranged from 14% [95% CI 7, 21%] at 24-25 weeks of gestation to 40% [95% CI 31, 47%] at 28-31 weeks. Almost all reductions in gestational age- and birthweight-specific infant mortality between 1985-87 and 1992-94 were due to approximately equal reductions in neonatal and post-neonatal mortality. Live births > or = 42 weeks of gestation did not follow this rule; post-neonatal mortality rates among such live births decreased significantly by 51% [95% CI 26, 68%], although neonatal mortality rates showed no significant change. The mortality reductions observed across the gestational age and birthweight range are probably a consequence of specific clinical interventions complementing improvements in fetal growth. Temporal changes in the outcome of post-term pregnancies need to be carefully examined, especially in relation to recent changes in the obstetric management of such pregnancies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".