Association between echocardiographic parameters of cardiac structure and function and mild cognitive impairment
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases (CVDs) marked with cardiac morphological or hemodynamical abnormalities are associated with mild cognitive impairment (MCI). The links between cardiac structure and function and MCI are not well understood. We aimed to explore the association between echocardiographic parameters of cardiac structure and function and MCI in CVD patients. METHODS: We conducted an age-, gender-, and education level-matched case-control study in general CVD participants with a 1:3 ratio of MCI (Montreal Cognitive Assessment [MoCA] score < 26 and Mini-Mental State Examination [MMSE] score ≥ 24) and cognitively normal participants at a tertiary hospital in Beijing, China. The echocardiographic cardiac parameters and cognitive status were retrieved through the clinical electronic database from May 2021 to August 2023. Principal component analysis (PCA), negative binomial, and conditional multivariate regression were performed. RESULTS: A total of 1136 CVD participants (mean age, 61.2 ± 8.3 years) were included in the study, comprising 289 (25.3%) MCI and 847 cognitively normal participants. Compared to cognitively normal participants, MCI participants had a higher prevalence of left ventricular (LV) diastolic dysfunction (54.0% vs. 40.3%; P < 0.001) and greater interventricular septal thickness (IVST) (1.04 ± 0.20 cm vs. 1.00 ± 0.17 cm; P = 0.002). LV diastolic dysfunction (Beta [SE], 0.234 [0.045]; P < 0.001) and IVST (Beta [SE], 0.034 [0.016]; P = 0.036) were negatively correlated with the MoCA score of global cognitive function. LV diastolic dysfunction (OR, 2.03; 95% CI, 1.48-2.79; P < 0.001) and IVST (OR, 1.14; 95% CI, 1.03-1.27; P = 0.014) were positively associated with MCI, independent of diagnosed CVDs and the conventional MCI risk factors. CONCLUSIONS: General CVD patients with abnormal echocardiographic LV diastolic dysfunction and IVST were associated with cognitive decline, suggesting further cognitive assessment for MCI. TRIAL REGISTRATION: Retrospectively registered.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".