Cognitive impairment and risk of future stroke: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Several studies have assessed the link between cognitive impairment and risk of future stroke, but results have been inconsistent. We conducted a systematic review and meta-analysis of cohort studies to determine the association between cognitive impairment and risk of future stroke. METHODS: We searched MEDLINE and Embase (1966 to November 2013) and conducted a manual search of bibliographies of relevant retrieved articles and reviews. We included cohort studies that reported multivariable adjusted relative risks and 95% confidence intervals or standard errors for stroke with respect to baseline cognitive impairment. RESULTS: We identified 18 cohort studies (total 121 879 participants) and 7799 stroke events. Pooled analysis of results from all studies showed that stroke risk increased among patients with cognitive impairment at baseline (relative risk [RR] 1.39, 95% confidence interval [CI] 1.24-1.56). The results were similar when we restricted the analysis to studies that used a widely adopted definition of cognitive impairment (i.e., Mini-Mental State Examination score < 25 or nearest equivalent) (RR 1.64, 95% CI 1.46-1.84). Cognitive impairment at baseline was also associated with an increased risk of fatal stroke (RR 1.68, 95% CI 1.21-2.33) and ischemic stroke (RR 1.65, 95% CI 1.41-1.93). INTERPRETATION: Baseline cognitive impairment was associated with a significantly higher risk of future stroke, especially ischemic and fatal 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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".