Marker associations of chronic heart failure severity and cognitive dysfunction in elderly patients
Bibliographic record
Abstract
Introduction. Next to neurodegenerative disorders, cardiovascular diseases are now the most common cause of cognitive impairment. The combination of factors such as older age and chronic heart failure is a corner-stone of a greater risk for developing vascular cognitive impairment. Aim. To study the relationship between the parameters of the left ventricular ejection fraction and the concentration of NT-proBNP with the results of neuropsychological testing in patients with chronic heart failure in old age. Materials and methods . The study included 200 elderly patients with CHF II–III FC. The neuropsychological examination included tests: tracking, Schulte tables, verbal associations, the Montreal Cognitive Function Assessment Scale (МоСА test). Laboratory tests included determination of the concentration of NT-proBNP in serum. Results. During neuropsychological testing, reduced indicators were obtained: during the MOS test in patients with left ventricular ejection fraction (LVEF) values < 40% and ≥ 40% and < 50% and with a concentration of NT-proBNP 7230 [3325; 8830] pg/ml; in the Schulte test, an increase in execution time was noted in patients with LVEF values < 40% and ≥ 40% and < 50% and with a concentration of NT-proBNP 2900 [700; 7500] pg/ml; in the tracking test – an increase in time in part A in patients with LVEF values < 40% and ≥ 40% and < 50% and with a concentration of NT-proBNP 5385 [2125; 8675] pg/ml and part B in patients with LVEF values < 40% and ≥ 40% and < 50% and with a concentration of NT-proBNP 6947 [3325; 9310] pg/ml, in the verbal association test – in patients with LVEF values < 40% and ≥ 40% and < 50% and with a concentration of NT-proBNP 2090 [608; 7126] pg/ml. Correlation analysis showed the presence of a significant relationship between LVEF indicators, the concentration of NT-proBNP and the results of neuropsychological testing (p < 0.001), while, according to the Rea&Parker classification, the connection was assessed as relatively strong and medium strength. Conclusion. The cognitive impairments identified in this study in elderly patients with chronic heart failure were characterized by a decrease in concentration, memory, executive functions and the overall integrative index of cognitive functions. These disorders were significantly associated with a decrease in the left ventricular ejection fraction and a high concentration of NT-proBNP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".