Mild cognitive impairment is associated with subclinical diastolic dysfunction in patients with chronic heart disease
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Bibliographic record
Abstract
Background: To examine mild cognitive impairment and its associations with subclinical cardiac dysfunction in patients with chronic heart disease yet to develop the clinical syndrome of chronic heart failure (CHF). Methods and results: Patients from the Nurse-led Intervention for Less Chronic Heart Failure Study (n = 373 with chronic heart disease other than CHF; 64 ± 11 years, 69% men) were screened for mild cognitive impairment [Montreal cognitive assessment (MoCA) score <26] and underwent echocardiographic/clinical profiling. We investigated associations of mild cognitive impairment and MoCA cognitive domain subscores with global cardiac status ('normal' vs. 'diastolic dysfunction' vs. 'other cardiac abnormality') and individual echocardiographic parameters. Patients with mild cognitive impairment (n = 161; 43%) demonstrated a higher age-adjusted prevalence of diastolic dysfunction (37% vs. 24%; P < 0.05). Multivariate logistic regression (adjusted for age, sex, and other relevant clinical factors) indicated that the odds of mild cognitive impairment were two-times higher with diastolic dysfunction (P = 0.030) and 1.7-times higher with 'other cardiac abnormalities' (P = 0.082) vs. normal cardiac status. In turn, mild cognitive impairment was predicted by left-ventricular (LV) filling pressure (based on the ratio of early diastolic filling and annular velocities; adjusted odds ratio 1.07 per unit increase, P = 0.022), but not LV structural parameters. Specific deficits in the cognitive domains of executive functioning and visuo-constructional abilities were also independently predicted by diastolic dysfunction (P < 0.05). Conclusion: Mild cognitive impairment is prevalent in patients with subclinical chronic heart disease at high-risk of CHF. Independent associations with LV diastolic dysfunction suggest a link between cardiac and cognitive functioning beyond shared risk factors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it