Risk factors for delayed-onset dementia after stroke or transient ischemic attack—A five-year longitudinal cohort study
Bibliographic record
Abstract
BACKGROUND: Stroke not only substantially increases the risk of incident dementia early after stroke but also the risk remains elevated years after. AIM: We aimed to determine the risk factors of dementia onset more than three to six months after stroke or transient ischemic attack. METHODS: This is a single-center prospective cohort study. We recruited consecutive subjects with stroke/transient ischemic attack without early-onset dementia. We conducted an annual neuropsychological assessment for five years. We investigated the association between baseline demographic, clinical, genetic (APOEɛ4 allele), and radiological factors as well as incident recurrent stroke with delayed-onset dementia using Cox proportional hazards models. RESULTS: In total, 1007 patients were recruited, of which 88 with early-onset dementia and 162 who lost to follow-ups were excluded. Forty-nine (6.5%) out of 757 patients have incident delayed-onset dementia. The presence of ≥3 lacunes, history of ischemic heart disease, history of ischemic stroke, and a lower baseline Hong Kong version of the Montreal Cognitive Assessment (MoCA) score were significantly associated with delayed-onset dementia. APOEɛ4 allele, medial temporal lobe atrophy, and recurrent stroke were not predictive. CONCLUSION: The presence of ≥3 lacunes, history of ischemic heart disease, history of ischemic stroke, and a lower baseline MoCA score are associated with delayed-onset dementia after stroke/transient ischemic attack.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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".