Epidemiological investigation of a temporal increase in atonic postpartum haemorrhage: a population‐based retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: Increases in atonic postpartum haemorrhage (PPH) have been reported from several countries in recent years. We attempted to determine the potential cause of the increase in atonic and severe atonic PPH. DESIGN: Population-based retrospective cohort study. SETTING: British Columbia, Canada, 2001-2009. POPULATION: All women with live births or stillbirths. METHODS: Detailed clinical information was obtained for 371 193 women from the British Columbia Perinatal Data Registry. Outcomes of interest were atonic PPH and severe atonic PPH (atonic PPH with blood transfusion ≥1 unit; atonic PPH with blood transfusion ≥3 units or procedures to control bleeding), whereas determinants studied included maternal characteristics (e.g. age, parity, and body mass index) and obstetrics practice factors (e.g. labour induction, augmentation, and caesarean delivery). Year-specific unadjusted and adjusted odds ratios for the outcomes were compared using logistic regression. MAIN OUTCOME MEASURES: Atonic PPH and severe atonic PPH. RESULTS: Atonic PPH increased from 4.8% in 2001 to 6.3% in 2009, atonic PPH with blood transfusion ≥1 unit increased from 16.6 in 2001 to 25.5 per 10 000 deliveries in 2009, and atonic PPH with blood transfusion ≥3 units or procedures to control bleeding increased from 11.9 to 17.6 per 10 000 deliveries. The crude 34% (95% CI 26-42%) increase in atonic PPH between 2001 and 2009 remained unchanged (42% increase, 95% CI 34-51%) after adjustment for determinants of PPH. Similarly, adjustment did not explain the increase in severe atonic PPH. CONCLUSIONS: Changes in maternal characteristics and obstetric practice do not explain the recent increase in atonic and severe atonic PPH.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".