Fatal Obstetrical Hemorrhage: A 20-Year Analysis From Ontario
Bibliographic record
Abstract
OBJECTIVES: Obstetric hemorrhage is a leading cause of pregnancy-related death. This study examined the characteristics, subtypes, and timing of obstetrical hemorrhagic deaths within a universal health care system. METHODS: Secondary analysis of a retrospective cohort study of linked administrative data, in which 485 post-pregnancy deaths over a 20-year period were identified. Obstetric hemorrhage deaths within 365 days of birth were reviewed by at least 3 clinicians to determine the main cause and timing of death. RESULTS: Of 485 post-pregnancy deaths, 46 (9.5%) were attributed to obstetric hemorrhage, representing 27% of pregnancy-related deaths (46 of 169). All 46 obstetric hemorrhage deaths occurred within 12 days postpartum, with 26 deaths (56.5%) on the day of delivery. The top causes of fatal obstetrical hemorrhage were 9 (19.6%) amniotic fluid embolisms, 6 (13.0%) placental abruptions, and 5 (10.9%) uterine ruptures; but in 14 (30%) cases, the main cause was uncertain. Of all fatal hemorrhages, 3 (6.5%) began antepartum, 17 (37.0%) intrapartum, and 20 (43.5%) postpartum. Deaths were higher in more materially deprived neighbourhoods (39.1% in quintile 5 vs. 6.5% in quintile 1). Obstetric hemorrhage deaths were highest for Sunday deliveries (3.7 per 100 000 births, rate ratio 3.8; 95% CI 0.8-18.8), followed by Monday deliveries (2.7 per 100 000, rate ratio 2.7; 95% CI 0.5-13.9). CONCLUSIONS: Obstetric hemorrhage remains a major contributor to pregnancy-related deaths, with most fatalities occurring very early postpartum. This study provides important insights into maternal post-pregnancy deaths due to obstetric hemorrhage in Ontario over a 20-year period.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".