Fetal, Neonatal, and Infant Mortality Surveillance in Nova Scotia: A Population-Based Cohort Study Examining Temporal Trends From 1988 to 2022
Bibliographic record
Abstract
OBJECTIVES: To describe annual trends in the incidence of stillbirth and infant mortality in Nova Scotia over a 35-year period. METHODS: weeks gestation or ≥500 g were included. Rates of fetal death (per 1000 births) and neonatal and infant mortality (per 1000 live births) were calculated by birth year. Rates were reported for the entire cohort and stratified by birth parent age, birthweight for gestational age and sex, and number of fetuses. RESULTS: A total of 334 776 deliveries were included, with 332 975 of these being live births; there were 1801 stillbirths, 1082 neonatal deaths, and 1579 infant deaths. Rates of fetal, neonatal, and infant death decreased between 1988-1992 and 2018-2022 (6.8-4.8, 4.0-2.5, and 6.3-4.0 per 1000 births, respectively). Rates increased somewhat in later 5-year epochs among those ≥35 years of age. Rates in the <10th percentile of birthweight for gestational age were highest in earlier epochs and showed a general downward trend with each epoch except the last. Marked temporal reductions in rates among multiple gestations were observed. CONCLUSIONS: Increases in mortality in later epochs, and among select birth parents and infant factors, suggest that patient characteristics and clinical practice changes may play a role in these increases. The observed temporal changes are important in informing the evaluation of factors associated with stillbirth and infant mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".