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Record W4413842055 · doi:10.1093/ejcts/ezaf243

Antithrombotic therapy after coronary artery bypass graft surgery: a Clinical Consensus Statement of the ESC Working Group on Cardiovascular Surgery, the ESC Working Group on Cardiovascular Pharmacotherapy, and the European Association for Cardio-Thoracic Surgery (EACTS)

2025· review· en· W4413842055 on OpenAlexaff
Sigrid Sandner, Mario Gaudino, Stefan Agewall, Giorgia Bonalumi, Nikolaos Bonaros, Martin Czerny, Anders Jeppsson, Milan Milojevic, Alexander Niessner, Alessandro Parolari, Patrick Sulzgruber, Juan Tamargo, Matthias Thielmann, Sven Waßmann, Alicja Zientara, Dobromir Dobrev

Bibliographic record

VenueEuropean Journal of Cardio-Thoracic Surgery · 2025
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineAntithromboticAspirinPharmacotherapyArteryClopidogrelPlatelet aggregation inhibitorCardiologyCoronary artery bypass surgeryBypass graftingSurgeryInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Antithrombotic therapy is essential after coronary artery bypass graft surgery to reduce ischaemic events and prevent graft occlusion. Although aspirin remains the most commonly used agent, in higher-risk patients, dual antiplatelet therapy or combining antiplatelet therapy with oral anticoagulation may be beneficial, but this increases bleeding risk. The choice of antithrombotic therapy should be tailored to each patient, based on their ischaemic and bleeding risks, and regularly reassessed. Here, the scientific evidence underlying the key aspects of the choice of antithrombotic therapy after coronary artery bypass grafting is reviewed. Consensus statements for best clinical practice are provided and areas requiring further research are highlighted.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.083
GPT teacher head0.336
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Cardio-Thoracic SurgerySame topicAntiplatelet Therapy and Cardiovascular DiseasesFrench-language works237,207