CHARACTERISTICS OF COGNITIVE FUNCTIONS DURING THE RECOVERY PERIOD AFTER ISCHEMIC STROKES IN PATIENTS WITH IMPAIRED CARDIAC RHYTHM AND CONDUCTION
Bibliographic record
Abstract
Introduction. Disturbances of cardiac rhythm and conduction are risk factors for cognitive impairments. Aim: to determine peculiarities of the cognitive status in patients with impaired heart rhythm and conduction during the recovery period after ischemic non-lacunar strokes. Material and methods. This study included 52 patients with atrial fibrillation, 18 patients with atrioventricular block 2-3 degrees, and 24 patients with sinus rhythm who had an ischemic non-lacunar stroke during the last 6 months. Cognitive status was measured using the MMSE, MoCA, ADAS-cog scales, the Clock Drawing Test, the “5 Words” test, and the frontal assessment battery. Results. According to the MoCA scale, patients with atrial fibrillation and atrioventricular block were significantly more often diagnosed with post-stroke cognitive impairments (71.2% and 77.8%, respectively) compared with patients having sinus rhythm (37.5%). Among patients with cognitive impairments by the MoCA scale, the presence of atrial fibrillation was associated with a significant decrease in MoCA scale scores, compared with sinus rhythm (18.0 (17.0-22.0) versus 22.0 (18.0-23.0)). In patients with sinus rhythm, the clock-drawing test had higher scores (8.0 (7.0-9.0)) compared to cases with atrial fibrillation (7.0 (5.8-8.0)). Patients with sinus rhythm had higher values of the frontal assessment battery (15.0 (14.0-15.0)) compared to atrial fibrillation (13.0 (12.0-14.0)) and atrioventricular blocks (14.0 (13.0- 15.0)). Conclusions. During the first 6 months after schemic non-lacunar strokes, patients with impaired heart rhythm and conduction demonstrated a significant prevalence of cognitive impairments by the MoCA scale and significantly worse scores of cognitive tests for executive functions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".