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Record W4406992609 · doi:10.1161/str.56.suppl_1.wmp101

Abstract WMP101: Atrial Cardiopathy Biomarkers and Brain Infarction in Multiple Territories in ARCADIA

2025· article· en· W4406992609 on OpenAlexaboutno aff
Rachel Gologorsky, Nilushi Karunamuni, W. T. Longstreth, David Tirschwell, Mitchell S Elkind, Hooman Kamel

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineArcadiaStroke (engine)Brain infarctionAtrial fibrillationCardiologyInfarctionInternal medicineMyocardial infarctionIschemia

Abstract

fetched live from OpenAlex

Introduction: The ARCADIA trial (Apixaban to Prevent Recurrence After Cryptogenic Stroke in Patients With Atrial Cardiopathy) found no benefit of anticoagulation for secondary stroke prevention in patients with cryptogenic stroke and evidence of atrial cardiopathy. It remains unclear if the biomarkers used in the trial reliably identified atrial cardiopathy. We examined the association between biomarkers of atrial cardiopathy and acute brain infarction in multiple arterial territories, an imaging signature of cardioembolic stroke. Hypothesis: Biomarkers of atrial cardiomyopathy are associated with acute brain infarction in multiple arterial territories. Methods: The ARCADIA trial screened patients with cryptogenic stroke for atrial cardiopathy at 185 centers in the U.S. and Canada. Investigators were asked to record the presence and topography of acute brain infarction on baseline imaging. Multi-territorial infarction was defined as acute infarction in at least two of the left middle cerebral artery (MCA), right MCA, and posterior circulation. P-wave terminal force in ECG lead V1 (PTFV1) and left atrial dimension index (LADI) were modeled as continuous variables, whereas N-terminal pro-B-type natriuretic peptide (NT-proBNP) was log-transformed. Relative risk regression was used to examine the association between atrial cardiopathy biomarkers and multi-territorial infarction. Results: Of 3,745 patients enrolled in ARCADIA, 3,301 had available data on atrial cardiomyopathy biomarkers and the topography of acute infarctions seen on baseline imaging. Of these 3,301 patients, 452 (13.7%) had multi-territory brain infarction. We found no association with multi-territory brain infarction for ln(NT-proBNP) (OR per SD, 1.06; 95% CI, 0.97-1.16), PTFV1 (OR per SD, 1.06; 95% CI, 0.98-1.15), or LADI (OR per SD, 0.95; 95% CI, 0.86-1.05). Patients who met criteria for atrial cardiopathy and were randomized into the treatment phase of the study had a similar likelihood of multi-territorial infarction (13.4%) compared with those who were not eligible for randomization (13.8%) (P = 0.77). Conclusions: The atrial cardiopathy biomarkers used in the ARCADIA trial were not associated with patterns of brain infarction suggestive of a cardioembolic source.

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 score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.246
Teacher spread0.239 · 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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