Epidemiological Studies of the Effect of Stroke on Incident Dementia
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Stroke is implicated in the incidence of dementia, and the risk of poststroke dementia is well characterized, but the excess risk of dementia in those with stroke compared with those without stroke is not well known. METHODS: We conducted a systematic review of the excess risk of incident dementia conferred by stroke. Studies of the risk of incident dementia in the population with stroke compared with the population without stroke were identified and compared. RESULTS: Sixteen studies were identified with all but one conducted in a community setting. A history of stroke doubles the risk of incident dementia in the older population. This increase is not explained by demographic or cardiovascular risk factors or by prestroke cognitive decline. The excess risk of incident dementia diminishes with time after stroke and may be higher in those without an APOE epsilon4 allele. There is no excess risk of incident dementia in those aged >85 years with a history of stroke compared to those aged >85 years without stroke. CONCLUSIONS: The effect of stroke on dementia incidence in the population is not explained by common risk factors. At this time of population aging and increased stroke survival, more research is needed to determine to what extent efforts to reduce the incidence of stroke will affect the incidence of dementia.
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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 | 0.010 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".