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Record W3142478671 · doi:10.1093/eurheartj/ehab196

Management of antithrombotic therapy in patients undergoing transcatheter aortic valve implantation: a consensus document of the ESC Working Group on Thrombosis and the European Association of Percutaneous Cardiovascular Interventions (EAPCI), in collaboration with the ESC Council on Valvular Heart Disease

2021· article· en· W3142478671 on OpenAlexaff
Jurriën M. ten Berg, Dirk Sibbing, Bianca Rocca, Éric Van Belle, Bernard Chevalier, Jean‐Philippe Collet, Dariusz Dudek, Martine Gilard, Diana A. Gorog, Julia Grapsa, Erik Lerkevang Grove, Patrizio Lancellotti, Anna Sonia Petronio, Andrea Rubboli, Lucia Torracca, Gemma Vilahur, Adam Witkowski, Julinda Mehilli

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Thomas Hospital
FundersDaiichi Sankyo EuropeBoston Scientific CorporationPfizerBristol-Myers Squibb
KeywordsMedicineAntithromboticPercutaneousCardiologyInternal medicineThrombosisConsensus conferencePsychological interventionPercutaneous coronary interventionSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

Transcatheter aortic valve implantation (TAVI) is effective in older patients with symptomatic severe aortic stenosis, while the indication has recently broadened to younger patients at lower risk. Although thromboembolic and bleeding complications after TAVI have decreased over time, such adverse events are still common. The recommendations of the latest 2017 ESC/EACTS Guidelines for the management of valvular heart disease on antithrombotic therapy in patients undergoing TAVI are mostly based on expert opinion. Based on recent studies and randomized controlled trials, this viewpoint document provides updated therapeutic insights in antithrombotic treatment during and after TAVI.

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)0.002
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 score0.007
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.032
GPT teacher head0.293
Teacher spread0.260 · 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

Citations142
Published2021
Admission routes1
Has abstractyes

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