MétaCan
Menu
Back to cohort
Record W4416153386 · doi:10.1001/jamacardio.2025.4151

Major Bleeding With Apixaban vs Aspirin

2025· article· en· W4416153386 on OpenAlexaff
Deborah Siegal, Christian Sticherling, Jeff S. Healey, William F. McIntyre, Lene Svendstrup Christensen, Ratika Parkash, Thomas Vanassche, David Conen, Michael R. Gold, Christopher B. Granger, Jens Cosedis Nielsen, Marc Carrier, Daniel Wojdyla, Julia W. Erath, Léna Rivard, Valentina Kutyifa, David J. Wright, Renato D. Lópes

Bibliographic record

VenueJAMA Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteMontreal Heart InstituteOttawa HospitalDalhousie UniversityUniversity of Ottawa
Fundersnot available
KeywordsApixabanAspirinAtrial fibrillationStroke (engine)Subclinical infectionRandomized controlled trialMajor bleeding

Abstract

fetched live from OpenAlex

Importance: The Apixaban for the Reduction of Thromboembolism in Patients With Device-Detected Subclinical Atrial Fibrillation (ARTESiA) randomized clinical trial showed that in patients with subclinical atrial fibrillation (SCAF) apixaban, compared with aspirin, reduced stroke/systemic embolism but increased major bleeding. Objectives: To characterize major bleeding events (site and severity) and identify factors associated with major bleeding. Design, Setting, and Participants: This was a prespecified subanalysis of the ARTESiA population who received treatment. This was an international, double-blind, double-dummy randomized clinical trial. Included were patients with 1 or more episodes of SCAF lasting 6 minutes to 24 hours with stroke risk factors (CHA2DS2-VASc score ≥3) or prior stroke without other risk factors. Study data were analyzed from August to November 2024. Interventions: Apixaban, 5 mg, twice daily (2.5 mg twice daily when indicated) or aspirin, 81 mg, once daily. Main Outcomes and Measures: Major bleeding adjudicated by a blinded committee according to International Society on Thrombosis and Hemostasis criteria. Results: A total of 3961 patients (mean [SD] age, 76.8 [7.6] years; 2535 male [64%]) were included in this analysis. After a mean (SD) follow-up of 3.5 (1.8) years, 1 or more major bleeding episodes occurred in 133 patients, 86 of 1989 taking apixaban and 47 of 1972 taking aspirin (1.71 vs 0.94 per 100-patient-years; hazard ratio [HR], 1.80; 95% CI, 1.26-2.57). The rates of intracranial (0.33 vs 0.40 per 100 patient-years; HR, 0.82; 95% CI, 0.43-1.57) and fatal (0.10% vs 0.16% per 100 patient-years; HR, 0.63; 95% CI, 0.20-1.91) bleeding were similar in the apixaban and aspirin groups, whereas the rate of gastrointestinal bleeding was higher in the apixaban group (0.89% vs 0.40% per 100 patient-years; HR, 2.23; 95% CI, 1.32-3.78). Among 133 index major bleeding events, those that occurred with apixaban were less likely to occur at critical sites (27.9% [24 of 86] vs 46.8% [22 of 47]; P = .03) including intracranial (18.6% [16 of 86] vs 42.6% [20 of 47]; P = .003). Most major bleeding events were nonemergencies characterized by decreased hemoglobin greater than or equal to 2 g/dL. Factors associated with major bleeding included nonsteroidal anti-inflammatory drug (NSAID) use (HR, 10.25; 95% CI, 6.57-15.99), cancer (HR, 2.87; 95% CI, 1.49-5.53), randomization to apixaban (HR, 1.84; 95% CI, 1.29-2.63), and age (HR, 1.47; 95% CI, 1.28-1.67, per 5-year increase). Conclusions and Relevance: Results of this subanalysis of the ARTESiA randomized clinical trial found that although the rate of major gastrointestinal bleeding was higher in patients with SCAF who were treated with apixaban vs aspirin, rates of fatal and intracranial bleeding were not different. Most major bleeding events were nonemergencies characterized by a decrease in hemoglobin level greater than or equal to 2 g/dL. NSAID use, cancer, randomization to apixaban, and increasing age were associated with an increased risk of major bleeding. Trial Registration: ClinicalTrials.gov Identifier: NCT01938248.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.423
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.314
Teacher spread0.284 · 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 teacher head, 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJAMA CardiologySame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207