Irregular Baseline Brain Activity in Coronary Artery Disease Patients withCognitive Impairment: A Resting-state Functional Magnetic ResonanceImaging Study
Bibliographic record
Abstract
OBJECTIVE: Cognitive impairment has been suggested to be associated with coronary artery disease [CAD]; however, the underlying mechanism is not fully understood. Our current study aimed to explore the brain activity in CAD patients compared to healthy controls [HCs]. METHODS: Twenty-two CAD patients and 23 HCs were enrolled in our study. A low-frequency oscillation at the voxel level in all participants based on the amplitude of low-frequency fluctuations [ALFF] was measured using resting-state functional magnetic resonance imaging. All participants underwent neuropsychological examinations [Mini-Mental State Examination, MMSE and Montreal Cognitive Assessment, MoCA] and visual acuity examination. RESULTS: CAD patients showed significantly lower ALFF values [P < 0.05] in the right precuneus gyrus [Precuneus_R], left supramarginal gyrus [Supramarginal_L], left angular gyrus [Angular_L], and left middle cingulum gyrus [Cingulum_Mid_L] than healthy controls. Lower MoCA scores in CAD patients significantly correlated with lower Supramarginal_L [P = 0.001] and Cingulate_ Mid_L [P = 0.004] ALFF values. Reduced visual acuity significantly correlated with lower Precuneus_R [P = 0.019] and Cingulate_Mid_L [P = 0.011] ALFF values in CAD patients. CONCLUSION: These findings may provide further insight into the underlying neuropathophysiology of CAD with cognitive impairment.
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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".