Severe obstetric maternal morbidity: a 15-year population-based study
Bibliographic record
Abstract
Using a provincial perinatal database for 15 years, 1988-2002. Cases were identified with one or more of the following markers of severe maternal morbidity: blood transfusion > or = 5 units, emergency hysterectomy, uterine rupture, eclampsia, intensive care (ICU) admission. There were 159,896 mothers delivered of whom 313 (2.0/1000) had 385 markers of severe morbidity (257 had one, 42 had two, 12 had three, and two had four). The following rates of morbidity were recorded: blood transfusion > or = 5 units 119 (0.74/1000); emergency hysterectomy 88 (0.55/1000); uterine rupture 49 (0.31/1000); eclampsia 46 (0.28/1000); ICU 83 (0.52/1000). There was a statistically significant association between multiparity > or = 1, and emergency hysterectomy and uterine rupture; between age > or = 35 years, and emergency hysterectomy, uterine rupture and ICU; and between caesarean delivery and blood transfusion > or = 5 units, emergency hysterectomy, uterine rupture, eclampsia and ICU. The main contributing obstetric complications were haemorrhage (64.7%) and complications of hypertensive disorders (16.8%).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".