Investigation of an increase in postpartum haemorrhage in Canada
Bibliographic record
Abstract
OBJECTIVE: To investigate the cause of a recent increase in hysterectomies for postpartum haemorrhage in Canada. DESIGN: Retrospective cohort study. SETTING: Canada between 1991 and 2004. POPULATION: All hospital deliveries in Canada as documented in the database of the Canadian Institute for Health Information (excluding incomplete data from Quebec, Manitoba and Nova Scotia). METHODS: Deliveries with postpartum haemorrhage by subtype were identified using International Classification of Diseases codes, while hysterectomies were identified using procedure codes. Changes in determinants of postpartum haemorrhage (all postpartum haemorrhage and that requiring hysterectomy) were examined, and crude and adjusted period changes were assessed using logistic models. MAIN OUTCOME MEASURES: Postpartum haemorrhage, postpartum haemorrhage with hysterectomy, postpartum haemorrhage with blood transfusion and postpartum haemorrhage by subtype. RESULTS: Rates of postpartum haemorrhage increased from 4.1% in 1991 to 5.1% in 2004 (23% increase, 95% CI 20-26%), while rates of postpartum haemorrhage with hysterectomy increased from 24.0 in 1991 to 41.7 per 100,000 deliveries in 2004 (73% increase, 95% CI 27-137%). These increases were because of an increase in atonic postpartum haemorrhage, from 29.4 per 1000 deliveries in 1991 to 39.5 per 1000 deliveries in 2004 (34% increase, 95% CI 31-38%). Adjustment for temporal changes in risk factors did not explain the increase in atonic postpartum haemorrhage but attenuated the increase in atonic postpartum haemorrhage with hysterectomy. CONCLUSIONS: There has been a recent, unexplained increase in the frequency, and possibly the severity, of atonic postpartum haemorrhage in Canada.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".