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Record W7127644136 · doi:10.1093/eurheartj/ehaf784.431

Brain atrophy and cognitive function in atrial fibrillation: a subanalysis of the SKAF study

2025· article· en· W7127644136 on OpenAlexaboutno aff
Toshinori Chiba, Y K Kondo, K Senoo, M N Nakano, T K Kajiyama, Y K Kobayashi

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAtrial fibrillationCognitionMontreal Cognitive AssessmentAtrophyMagnetic resonance imagingObservational studyStroke (engine)Sinus rhythmCognitive decline

Abstract

fetched live from OpenAlex

Abstract Background Cognitive function in patients with non-valvular atrial fibrillation (NVAF) tends to decline compared to patients without NVAF, even in the absence of symptomatic stroke or overt dementia. While previous studies have suggested an association between NVAF, and silent cerebral ischemia and microbleeds, the mechanisms linking NVAF to cognitive impairment remain unclear. Brain atrophy has been hypothesized as a potential contributor to cognitive dysfunction in NVAF patients, but its impact and clinical significance require further investigation. This study aimed to evaluate the relationship between brain atrophy and cognitive function in patients with NVAF. Methods The SKAF study is a prospective, investigator-initiated, multicenter, observational study involving Japanese patients with NVAF aged 60 years or older. We planned to enroll 200 NVAF patients with no history of symptomatic stroke or dementia, including those receiving anticoagulant therapy with edoxaban or not, and 100 patients with sinus rhythm for comparison. Participants underwent brain magnetic resonance imaging (MRI) and cognitive function assessment, including the Montreal Cognitive Assessment (MoCA), at enrollment and after 24 months. We analyzed cerebral atrophy using MRI. Results The study enrolled 310 patients (age: 72.1±6.5 years; male: 191 [61.6%]; NVAF: 213 [68.7%]). The mean CHA2DS2-VASc score in the NVAF group was 2.6±1.2. There was no significant difference between the NVAF group and the control group in the prevalence of silent ischemic stroke or silent microbleeds on MRI across the entire cohort. At enrollment, there was no significant difference in the MoCA score between the two groups (NVAF: 24.4±3.4, control: 25.2±2.9, P=0.054), and no difference in the extent of gray matter atrophy (NVAF: 3.5±1.6%, control: 3.4±2.1%, P=0.63). After 24 months, cognitive function in the NVAF group declined significantly compared to the control group (NVAF: 24.2±3.8, control: 25.5±3.2, P<0.01), while the extent of gray matter atrophy in the NVAF group remained no different from that in the control group (NVAF: 3.9±2.7%, control: 3.7±2.0%, P=0.68). Conclusion The extent of gray matter atrophy was not directly related to cognitive function in patients with NVAF. These findings suggest that brain atrophy may not be the primary driver of cognitive decline in NVAF, and other factors, such as microvascular dysfunction or neuroinflammatory processes, may play a more significant role.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.051
GPT teacher head0.341
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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