Neonatal Arterial Ischemic Stroke and Cerebral Sinovenous Thrombosis Are More Commonly Diagnosed in Boys
Bibliographic record
Abstract
The risk factors for arterial ischemic stroke and cerebral sinovenous thrombosis in neonates are not well understood. We looked at gender, birthweight, and gestational age in neonates with arterial ischemic stroke and cerebral sinovenous thrombosis to see if there were trends suggesting that these were risk factors. We identified neonates with a gestational age at birth > or = 36 weeks and a diagnosis of arterial ischemic stroke or cerebral sinovenous thrombosis made by computed tomography or magnetic resonance imaging during the neonatal period from a consecutive cohort study of children with arterial ischemic stroke and cerebral sinovenous thrombosis in Ontario. Data on gender, birthweight, and gestational age were obtained by health record review. Sixty-six children with neonatal arterial ischemic stroke were identified. Forty-one (62.1%; 95% CI 49.3-73.8%) were male. Thirty-two children with neonatal cerebral sinovenous thrombosis were identified. Twenty-five (78.1%; 95% CI 60.0-90.7%) were male. One male child was identified with both arterial ischemic stroke and cerebral sinovenous thrombosis. There was a trend toward higher than average birthweights among neonates with arterial ischemic stroke and a trend toward older gestational age in female neonates with arterial ischemic stroke. Our data suggest that neonatal arterial ischemic stroke and cerebral sinovenous thrombosis are more commonly diagnosed in boys. The slightly larger size of male neonates may be contributory in arterial ischemic stroke. It is not known whether boys are at higher risk of developing arterial ischemic stroke and cerebral sinovenous thrombosis or are simply more likely to present with symptoms resulting in diagnosis. These issues need further study.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".