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Record W7117256237 · doi:10.1002/alz70856_100246

Markers of left atrial cardiopathy for the prediction of dementia risk in aging adults: An analysis of Cardiovascular Health Study

2025· article· en· W7117256237 on OpenAlexaff
Zhe Li, Danielle Marion, Jessica Blair, Elsayed Z. Soliman, David J. Gladstone, Hooman Kamel, David H. Birnie, Doug Manuel, Virginia J. Howard, W.T. Longstreth, Oscar L Lopez, Jodi D. Edwards

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsOttawa HospitalInstitute for Clinical Evaluative SciencesUniversity of Ottawa
Fundersnot available
KeywordsDementiaCardiovascular healthClinical prediction ruleRisk assessmentHealthy agingRisk factor

Abstract

fetched live from OpenAlex

Abstract Background Atrial fibrillation (AF) is the most common cardiac arrhythmia. Several population‐based studies report associations between AF and dementia. Clinical AF is often preceded by substantive atrial structural and electrical remodeling, termed atrial cardiopathy and prior studies have shown that atrial cardiopathy is independently associated with dementia in the absence of AF. This study aims to develop and validate a prediction model for dementia risk using markers of atrial in addition to traditional vascular risk factors (i.e., CHA 2 DS 2 ‐VASc). Method This study utilized data from the Cardiovascular Health Study (CHS). A cohort of 3,608 participants who completed magnetic resonance imaging (MRI) and cognitive testing during 1992‐1994 were included for analysis. Markers of left atrial cardiopathy included left atrial dimension, p ‐wave terminal in lead V1 (PTFV1), and N‐Terminal pro‐Brain Natriuretic Peptide (NT‐pro BNP) level, all previously shown to be associated with left atrial function. Prediction models were built to estimate the predictive accuracy of combining markers of atrial cardiopathy with traditional clinical risk variables (CHA2DS2‐VASc) for dementia risk, in accordance with TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) prediction model recommendations. Result During a mean follow‐up of 7.6 years, 322 participants had incident dementia. Individuals with higher NT‐pro BNP levels had significantly higher cumulative incidence rates for incident dementia. Compared to the reference model, continuous PTFV1 and NT‐pro BNP level in both the categorical scale and log scale improved model fit for incident dementia in females. Compared to the reference model (CHA2DS2‐VASc), continuous NT‐pro BNP level improved model fit in males. Conclusion NT‐pro BNP, an emerging indicator of atrial cardiopathy, improves dementia risk prediction model fit compared to that obtained using the CHA2DS2‐VASc score. These findings have implications for dementia risk prediction and the development of screening tools for dementia prevention before the onset of clinical AF.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.032
GPT teacher head0.318
Teacher spread0.286 · 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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