Cognitive phenotypes and factors associated with cognitive decline in a cohort of older patients with atrial fibrillation: The <scp>Strat‐AF</scp> study
Bibliographic record
Abstract
Abstract Background and purpose The multifactorial relationship between atrial fibrillation (AF) and cognitive impairment needs to be elucidated. The aim of this study was to assess, in AF patients on oral anticoagulants (OACs), the prevalence of cognitive impairment, defined according to clinical criteria or data‐driven phenotypes, the prevalence of cognitive worsening, and factors associated with cognitive outcomes. Methods The observational prospective Strat‐AF study enrolled AF patients aged ≥ 65 years who were receiving OACs. The baseline and 18‐month protocol included clinical, functional, and cognitive assessment, and brain magnetic resonance imaging. Cognitive outcomes were: empirically derived cognitive phenotypes; clinical diagnosis of cognitive impairment; and longitudinal cognitive worsening. Results Out of 182 patients (mean age 77.7 ± 6.7 years, 63% males), 82 (45%) received a cognitive impairment diagnosis, which was associated with lower education level and functional status, and higher level of atrophy. Cluster analysis identified three cognitive profiles: dysexecutive (17%); amnestic (25%); and normal (58%). Compared to the normal group, the dysexecutive group was older, and had higher CHA2DS2‐VASc scores, while the amnestic group had worse cognitive and functional abilities, and medial temporal lobe atrophy (MTA). Out of 128 followed‐up patients, 35 (27%) had cognitive worsening that was associated with lower education level, worse cognitive efficiency, CHA2DS2‐VASc score, timing of OAC intake, history of stroke, diabetes, non‐lacunar infarcts, white matter hyperintensities and MTA. In multivariate models, belonging to the dysexecutive or amnestic group was a main predictor of cognitive worsening. Conclusions In our cohort of older AF patients, CHA2DS2‐VASc score, timing of OAC intake, and history of stroke influenced presence, type and progression of cognitive impairment. Empirically derived cognitive classification identified three groups with different clinical profiles and better predictive ability for cognitive worsening compared to conventional clinical diagnosis.
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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".