RELATIONSHIP BETWEEN COGNITIVE IMPAIRMENT AND LEFT VENTRICULAR DIASTOLIC DYSFUNCTION IN PATIENTS WITH HEART ARRHYTHMIAS.
Bibliographic record
Abstract
BACKGROUND: To estimate the relationship between cognitive function of patients with heart arrhythmias and left ventricle (LV) diastolic function. MATERIALS AND METHODS: In a one-center cross-control study we recruited 28 patients with heart arrhythmias, of whom 14 had 1800 or more premature ventricular contractions (PVCs) per 24 hours and more (group 1), and 14 had paroxysmal AF (group 2). All patients were asymptomatic for heart arrhythmias. Laboratory and instrumental methods included standard investigations: lipidograms, 24 hours ECG monitoring, transthoracic echocardiography (TTE), and, if prescribed, coronary angiography. In the TTE protocol, we followed current clinical recommendations in assessing the LV diastolic function. For cognitive function evaluation, we used the standard Montreal Cognitive Assessment (MoCA) test, with the following scoring: maximum possible score - 30 points; mild cognitive impairment - 22-27 points; moderate cognitive impairment - 10-21 points; severe cognitive impairment - 0-9 points. RESULTS: The most common heart arrhythmias (frequent PVCs, paroxysmal AF) were associated with cognitive impairment in the preponderance of patients (mean score here). CONCLUSIONS: LV diastolic dysfunction is a predictor for cognitive impairment in patients with frequent PVCs and paroxysmal AF. The MoCA test can be an additional tool for this category of patients to detect the early 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".