Cause-specific mortality during and after pregnancy and the definition of maternal death.
Bibliographic record
Abstract
As part of a study to determine whether maternal mortality in Canada is under- reported, we explored the validity of including deaths not directly related to pregnancy. We linked live birth and stillbirth registrations to death registrations of women of reproductive age from 1988 through 1992. We calculated standardized mortality ratios, by cause, from deaths in women known to have been pregnant and deaths in same-aged women not known to have been pregnant within the same time period. Women known to have been pregnant were approximately half as likely to die as would be expected in each of two six-month time periods: from 20 weeks gestation to 42 days postpartum (SMR 0.4, 95% CI 0.3-0.5), and from 42 days to 225 days postpartum (SMR 0.5, 95% CI 0.5-0.6). Furthermore, pregnant and recently pregnant women were not more likely to die from specific causes, with the exception of diseases of the arteries, arterioles, and capillaries (SMR 3.5, 95% CI 1.3-7.7) during pregnancy or within 42 days of pregnancy termination. The only other SMR that was > 1 was for death from cerebrovascular disorders during pregnancy and up to 42 days postpartum, although not significantly so (SMR 1.4, 95% CI 0.8-2.2). No other cause-specific SMRs were > 1. Moreover, recently pregnant women were found to be much less likely to commit suicide or to be the victims of homicide. We found no empirical justification for including deaths not directly related to pregnancy in reported counts of maternal deaths for most of the causal categories we considered.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| 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".