Abstract 2645: Functional Outcome in Young Adults after First-Ever Ischemic Stroke: A Particular Impact of Lipoproteins
Bibliographic record
Abstract
Background and Purpose: We aimed to determine functional outcome in a cohort of young adults with ischemic stroke, focusing on components of lipid profile. Methods: In our registry including consecutive patients with first-ever ischemic stroke aged 15 to 49 from 1994-2007, we analyzed predictors of 3-month functional outcome (modified Rankin Scale, mRS). Infarct size fell into small, medium, large posterior, or large anterior. Stroke severity was assessed with NIH Stroke Scale (NIHSS). Serum lipids were measured within 72 h after admission. Binary, multinomial ordinal, and Poisson regressions allowed revealing factors associated with size of infarct, stroke severity, and unfavorable outcome or death (mRS, 2-6) or mRS as an ordinal measure. Results: In the 968 patients included (mean age 41.3±7.6; 62.6% males; 49.5% with mRS 0-1), factors associated with unfavorable outcome after multivariable analysis were increasing age (odds ratio 1.03 per year, 95% confidence interval 1.01-1.05), higher NIHSS score (1.22 per point, 1.16-1.29), large anterior infarcts (4.51, 2.22-9.17), bilateral lesions (2.61, 1.43-4.77), internal carotid artery dissection (ICAD) (3.45, 1.29-9.19), large-artery atherosclerosis (2.30, 1.03-5.11), and inversely high-density lipoprotein (HDL) levels (0.59 per unit increase, 0.39-0.89). Increasing HDL associated with smaller infarct size (0.70, 0.49-0.98) and higher levels of HDL and low-density lipoprotein (LDL) were both associated with a lower NIHSS score (0.81, 0.75-0.88 for HDL; 0.96, 0.93-0.99 for LDL) and lower 3-month mRS (0.65, 0.47-0.90 for HDL; 0.86, 075-0.98 for LDL). Conclusions: In addition to known prognosticators, ICAD and lower HDL levels were independently associated with adverse clinical outcomes in our young adult stroke cohort.
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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 | 0.000 |
| 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) | 0.002 | 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".