Impact of COVID-19 on mild vascular cognitive impairment in patients with atrial fibrillation: results of a three-year observational study
Bibliographic record
Abstract
The relationship between vascular cognitive impairment (VCI) and atrial fibrillation (AF) is mediated by multiple mechanisms, including vascular risk factors associated with a more severe course of COVID-19. Objective: to investigate the impact of COVID-19 on the dynamics of cognitive status parameters in patients with AF over an observation period of 36 months. Material and methods. The observational study included 51 patients (19 men and 32 women; age ranged from 46 to 73 years, mean age 57.7 years) who met the inclusion criteria. All study participants were tested at baseline and after 36 months using Montreal Cognitive Assessment (MoCA). The study took place during COVID-19 pandemic, and 25.5% of patients had documented SARS-CoV-2-associated pneumonia. During the observation period, patients received stable background therapy to prevent modifiable vascular risk factors. Two groups were formed: group 1 (n=13) — COVID-19 “+”, group 2 (n=38) — COVID-19 “-”. Patients in group 1 were more likely to have stage IIIarterialhyper-tension (46.2% vs. 17.9% in group 2; p<0.05), had a history of ischemic stroke (38.5% vs. 5.3% in group 2; p<0.05), were not vaccinated with Gam-COVID-Vac vaccine (23.1% vs. 73.7% in group 2; p<0.05). Results. Patients with AF after SARS-CoV-2 virus infection experienced deterioration of VCI from 22.7±2.1 to 20.2±1.6 points according to MoCA (p<0.05) due to impairments in executive functions, attention, memory and speech. After 36 months of observation, the number of patients with a memory index score <7 points, which indicates a high risk of conversion of mild cognitive impairment to dementia, increased by 30.7% in group 1 and by 5.3% in group 2 (p<0.05). Conclusion. Patients with atrial fibrillation who had COVID-19 showed a more pronounced progression of cognitive impairment despite the constant use of stable background therapy aimed at correcting modifiable vascular risk factors.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".