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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".