P.017 Ischemic stroke in young adults: a comparison of outcomes, stroke risk factors and etiologies between males and females
Bibliographic record
Abstract
Background: The primary aim was to determine if functional outcomes among young adults with stroke differed based on sex. The secondary aim was to identify differences in stroke risk factors and etiologies between females and males. Methods: Retrospective analysis of acute ischemic stroke patients aged 18 to 55 years from a stroke registry between 2018 to 2022. Multivariable logistic regression to analyse if modified Rankin Scale at 3-6 months (mRS, 0-2 versus 3-6) was associated with sex. Results: 315 patients (127 female), median age 48 years (IQR 42-52), median NIHSS 10 (IQR 4-19, median mRS (3-6 months) 2 (IQR 1-3). Following adjustment for vascular risk factors, clinical stroke characteristics, baseline mRS and stroke time metrics no significant difference in mRS (3-6 months) based on sex (p=0.40). Females more frequently had an unknown time of stroke onset (p=0.03). Large-artery atherosclerosis as a stroke etiology (p=0.01), known atrial fibrillation (p=0.03) and drug use (p=0.003) were more frequent in males. Conclusions: Patient-oriented outcomes maybe of interest in future studies as functional mRS outcomes do not differ between young male and female stroke patients. Males had a higher prevalence of large-artery atherosclerosis and risk factors including drug use and atrial fibrillation. These findings could help develop targeted stroke prevention strategies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.007 | 0.001 |
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".