Stroke and Cerebrovascular Disease in Pregnancy
Bibliographic record
Abstract
Background and Purpose— Few studies have examined the epidemiology of stroke in pregnancy, despite the high associated burden of death and disability. We aimed to quantify the incidence, temporal trends, risk factors, and case fatality associated with stroke and cerebrovascular disease in pregnancy. Methods— All antepartum, peripartum, and postpartum hospitalizations and readmissions within 42 days of delivery in Canada (except Quebec) were obtained from the Canadian Institute of Health Information for the years 2003 to 2016. We assessed temporal trends in stroke and quantified associated risk factors using logistic regression. Results— Five hundred twenty-four stroke cases were identified among 3 907 262 deliveries (13.4 per 100 000). The majority of cases were hemorrhagic strokes (307 cases, 58.6%) and most occurred in the postpartum period (270 cases, 51.5%). The case fatality rate was 7.4%. Stroke incidence rose from 10.8 per 100 000 in 2003 to 2004 to 16.6 per 100 000 deliveries in 2015 to 2016 ( P =0.002). Risk factors for stroke included older maternal (age ≥40 years; adjusted odds ratio [AOR], 1.7; 95% CI, 1.1–2.6), preeclampsia (AOR, 7.1; 95% CI, 5.3–9.6), eclampsia (AOR, 65.9; 95% CI, 43.6–99.6), maternal congenital heart disease (AOR, 38.1; 95% CI, 22.1–65.8), connective tissue disorders (AOR, 12.6; 95% CI, 6.1–26.9), sepsis (AOR, 7.6; 95% CI, 3.6–16.2), severe postpartum hemorrhage (AOR, 4.7; 95% CI, 2.8–8.0), and thrombophilia (AOR, 4.2; 95% CI, 1.5–12.1). Conclusions— The rising incidence of stroke in pregnancy, especially during the postpartum period, and its strong association with hypertensive disorders of pregnancy (especially preeclampsia) suggest that follow-up of severe hypertensive patients is required after delivery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".