Cognitive function and outcomes post-stroke: a five-year follow-up of the ASPIRE-S cohort
Bibliographic record
Abstract
Introduction: Impairments in cognitive function are common following stroke and can increase disability and levels of dependency, resulting in increased burden on family members or carers, as well as the healthcare system. The aims of this study were to examine cognitive function trajectories in a cohort of stroke patients from six months to five years post-stroke, and to explore the outcomes associated with post-stroke cognitive decline. Methods: 5-year follow-up of the ASPIRE-S (Action on Secondary Prevention Interventions and Rehabilitation in Stroke) cohort study of stroke patients, involving a detailed assessment of cognitive function, secondary prevention and health care utilisation. 256 patients were last assessed at six months post-stoke, with c.180 being reassessed at 5-year follow up. Logistic regression analysis is based on data from the first half of this follow-up study. Findings: Out of 256 patients last seen six months post-stroke, 52 (20.3%) had died at 5-year follow-up. Cognitive impairment (MoCA <26) at six months was significantly associated with death at five years (aOR 2.98, 95%CI 1.12 to 7.91), controlling for age, modified Rankin Scale assessed 72 hours post-stroke, and number of cardiovascular risk factors. Associations between cognitive decline and secondary prevention, recurrent events, and costs in terms of quality of life and healthcare utilisation, will also be presented. Discussion: Post-stroke cognitive impairment is associated with mortality at five years, highlighting the potential importance of cognitive interventions and rehabilitation post-stroke.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".