Cardiovascular risk factors are associated with cognitive trajectory in the first year after stroke
Bibliographic record
Abstract
Introduction: Stroke often leads to cognitive impairment, but its progression and influencing factors over time remain poorly understood. This study evaluates immediate post-stroke cognitive impacts and investigates the influence of concurrent factors on cognitive evolution over the first year. Patients and methods: In the STRATEGIC study, 179 patients with first symptomatic ischemic stroke underwent neuropsychological assessments within three months post-stroke, and 141 were re-evaluated at 12 months. Risk factors tested for associations with cognitive outcome included demographic variables, cardiovascular and other medical factors, and lesion characteristics. Cognitive performance was primarily measured via the Montreal Cognitive Assessment (MoCA), with domain-specific assessments for episodic memory (Free and Cued Selective Reminding Task), short-term memory (Digit Span forward), and working memory (Digit Span backward). Results: = 9.5) and 36.9% were female. Ischemic heart disease predicted cognitive non-improvement between 3 and 12 months. Atrial fibrillation and carotid stenosis were linked to changes in episodic and working memory, respectively. Moreover, female sex and lower education correlated with stagnant global cognition and episodic memory. Discussion and conclusion: Our findings underscore the important influence of cardiovascular risk factors on cognitive functional recovery after stroke. Interventions targeting these risk factors may improve cognitive prognosis and affect traditional outcome measures such as recurrent vascular events. Future trials should include cognitive measures to fully capture the potential benefits of intensive risk factor intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".