Frequency and spatial characteristics of EEG in patients with coronary artery disease with preserved cognitive status and cognitive disorders
Bibliographic record
Abstract
Objective. The objective of this study was to investigate the effect of coronary artery disease (CAD) on the frequency and spatial characteristics of the electroencephalogram (EEG) in patients with preserved cognitive status and those with cognitive impairment. Material and methods. The study included 132 patients with stable coronary artery disease and 63 subjects in a group of apparently healthy elderly people. All patients underwent neuropsychological screening, and based on the results, they were divided into two groups: those without cognitive impairment (CI) who scored 27—30 points on the Montreal Cognitive Assessment Scale (MoCA) (n=37) and those with CI who scored 20—26 points on the MoCA scale (n=95). Patients and healthy subjects also underwent a high-resolution EEG. Results. It was found that the differentiation between groups of CAD patients with and without CI and healthy elderly individuals occurs at the frequencies of theta1, theta2, and alpha2 rhythms, with local differences in the power of theta1 biopotentials and global differences in the theta2 and alpha2 ranges. Conclusion. The presented results demonstrate that patients with CAD and cognitive impairment exhibit specific features in the frequency and spatial characteristics of brain electrical activity compared to those of healthy elderly 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".