Young Women Have Poorer Outcomes than Men after Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Gender differences in stroke outcome have not been fully assessed in young patients. METHODS: We conducted an observational study of consecutive young ischemic stroke patients (≤ 50 years of age) admitted to a stroke unit (January 1999 to December 2009). Basal data, subtype of ischemic stroke, stroke severity [Canadian Neurological Scale (CNS)], length of hospital stay, inhospital complications, mortality and functional outcome at discharge [modified Rankin Scale (mRS) score] were analyzed. For stroke severity and outcome analyses, 2 age groups were established: 15-30 (very young group) and 31-50 years old (middle-aged young group). RESULTS: A total of 310 patients were enrolled; 128 females and 182 males. The mean age was similar in women and men (41.07 ± 8.6 vs. 42.12 ± 8.2, NS). Migraine was more frequent in women, whereas arterial hypertension, hyperlipidemia, alcohol abuse, current smoking and atherothrombotic infarction were more frequent in men (p < 0.05). Females presented greater stroke severity than men [median CNS (IQR) = 8 (3.5) vs. 9 (2.5), p = 0.014] except in the very young group [median CNS (IQR) = 9 (1.8) vs. 8 (5), p = 0.022]. Female sex was a predictor of unfavorable outcomes (mRS >2) at discharge in the total sample (OR = 3.33; 95% CI = 1.41-7.84) and in the middle-aged young group (OR = 2.62; 95% CI = 1.05-6.53), adjusted by baseline data, stroke subtype, inhospital complications, length of stay and stroke severity. CONCLUSIONS: Female gender is associated with worse outcomes in adult ischemic stroke patients up to 50 years old. However, this effect is not observed in younger patients (15-30 years).
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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 | 0.001 |
| 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 | 0.001 |
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".