Cognitive impairment and risk of cardiovascular events and mortality
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment may increase the risk of all cardiovascular (CV) events. We prospectively evaluated the independent association between Mini-Mental State Examination (MMSE) score and myocardial infarction, stroke, hospital admission for heart failure and mortality, and their CV composite (major CV events), in a large high-risk CV population. METHODS AND RESULTS: Mini-Mental State Examination was recorded at baseline in 30 959 individuals enrolled into two large parallel trials of patients with prior cardiovascular disease or high-risk diabetes and followed for a median of 56 months. We used a Cox regression model to determine the association between MMSE score and incident CV events and non-CV mortality, adjusted for age, sex, education, history of vascular events, dietary factors, blood pressure, smoking, glucose, low-density lipoprotein, high-density lipoprotein, CV medications, exercise, alcohol intake pattern, depression, and psychosocial stress. Patients were categorized into four groups based on baseline MMSE; 30 (reference), 29-27, 26-24, and <24. Compared with patients with an MMSE of 30 (n = 9624), those with scores of 29-27 [n = 13 867; hazard ratio (HR) 1.08; 95% confidence intervals (CI) 1.01-1.16], 26-24 (n = 4764; HR: 1.15; 95% CI: 1.05-1.26) and <24 (n = 2704; HR: 1.35; 95% CI: 1.21-1.50) had a graded increase in the risk of major vascular events (P < 0.0001). Mini-Mental State Examination score was significantly associated with each of the individual components of the composite, except myocardial infarction. There was also no association between baseline MMSE and hospitalization for unstable or new angina. Within MMSE domains, impairments in orientation to place (HR: 1.52; 1.25-1.85), attention-calculation (HR: 1.10; 1.02-1.18), recall (HR: 1.10; 1.04-1.16), and design copy (HR: 1.15; 1.06-1.24) were the most predictive of major vascular events and mortality. The magnitude of increased risk of CV events associated with an MMSE <24 was similar to a previous history of stroke. CONCLUSION: In people at increased CV risk, impairments on baseline cognitive testing are associated with a graded increase in the risk of stroke, congestive heart failure, and CV death, but not coronary events. An MMSE score of <24 increased CV disease risk to the same extent as a previous 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".