Associations Between Cardiac Function and Brain Health in Diverse Middle-Aged Adults
Bibliographic record
Abstract
Previous studies have linked cardiovascular risk factors during midlife to cognitive function in later life. However, few studies have looked at the association between cardiac function, brain structure, and cognitive function and even less have included diverse middle-aged populations. The objective of this study was to determine associations between cardiac and brain structure and function in a multiethnic cohort of middle-aged adults. A cross-sectional study was conducted in participants of the Dallas Heart Study phase 2 (N = 1,919; 46% Black participants). Left ventricular (LV) mass, LV ejection fraction, LV concentricity, and peak systolic strain (LV Ecc) were assessed by cardiac magnetic resonance imaging. White matter hyperintensities (WMH) volume was measured by fluid attenuated inversion recovery magnetic resonance imaging. The Montreal Cognitive Assessment was used to measure cognitive functioning. Associations between cardiac and brain measures were determined using multivariable linear regression after adjusting for cardiovascular risk factors, education level, and physical activity. LV ejection fraction was associated with total Montreal Cognitive Assessment score (β = 0.06 [95% CI: 0.003-0.12], P = 0.042) and LV Ecc was associated with WMH volume (β = 0.08 [95% CI: 0.01-0.14], P = 0.025) in the overall cohort without significant interaction by race/ethnicity. Higher LV mass and concentricity were associated with larger WMH volume in the overall cohort (β = 0.13 [95% CI: 0.03-0.23], P = 0.008 and 0.10 [95% CI: 0.03-0.17], P = 0.005). These associations were more predominant in Black than White participants (β = 0.17 [95% CI: 0.04-0.30] vs β = −0.009 [95% CI: −0.16 to 0.14], P = 0.036 and β = 0.22 [95% CI: 0.13-0.32] vs β = −0.11 [95% CI: −0.21 to −0.01], P < 0.0001, for LV mass and concentricity, respectively). Subclinical cardiac dysfunction indicated by LVEF was associated with lower cognitive function. Moreover, LV mass and concentric remodeling were associated with higher WMH burden, particularly among Black individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".