Postpartum Period Is a Risk Factor for Cerebral Venous Thrombosis
Bibliographic record
Abstract
Background and Purpose- Pregnancy and the postpartum period are generally considered to be risk factors for cerebral venous thrombosis (CVT), but no controlled studies have quantified the risk. Methods- Case-control study using data of consecutive adult patients with CVT from 5 academic hospitals and controls from the Dutch MEGA study (Multiple Environmental and Genetic Assessment of risk factors for venous thrombosis). Men, women over the age of 50, women using oral contraceptives or with a recent abortion or miscarriage were excluded. We adjusted for age and history of cancer, and stratified for pregnancy versus postpartum, and 0 to 6 versus 7 to 12 weeks postpartum. Results- In total 163/813 cases and 1230/6296 controls were included. Cases were younger (median 38 versus 41 years) and more often had a history of cancer (14% versus 4%) than controls. In total 41/163 (25%) cases and 82/1230 (7%) controls were pregnant or postpartum (adjusted odds ratio, 3.8; 95% CI, 2.4-6.0). The association was fully attributable to an increased risk of CVT during the postpartum period (adjusted odds ratio, 10.6; 95% CI, 5.6-20.0). We found no association between pregnancy and CVT (adjusted odds ratio, 1.2; 95% CI, 0.6-2.3). The risk was highest during the first 6 weeks postpartum (adjusted odds ratio, 18.7; 95% CI, 8.3-41.9). Conclusions- Women who have recently delivered are at increased risk of developing CVT, while there does not seem to be an increased risk of CVT during pregnancy.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".