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Record W4361001980 · doi:10.1016/j.jscai.2022.100577

SCAI/HRS Expert Consensus Statement on Transcatheter Left Atrial Appendage Closure

2023· article· en· W4361001980 on OpenAlexaff
Jacqueline Saw, David R. Holmes, João L. Cavalcante, James V. Freeman, Andrew M. Goldsweig, Clifford J. Kavinsky, Issam Moussa, Thomas M. Munger, Matthew J. Price, Mark Reisman, Matthew W. Sherwood, Zoltan G. Turi, Dee Dee Wang, Brian Whisenant

Bibliographic record

VenueJournal of the Society for Cardiovascular Angiography & Interventions · 2023
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsClosure (psychology)AppendageStatement (logic)MedicineCardiologyInternal medicinePolitical scienceAnatomyLaw

Abstract

fetched live from OpenAlex

Exclusion of the left atrial appendage to reduce thromboembolic risk related to atrial fibrillation was first performed surgically in 1949. Over the past 2 decades, the field of transcatheter endovascular left atrial appendage closure (LAAC) has rapidly expanded, with a myriad of devices approved or in clinical development. The number of LAAC procedures performed in the United States and worldwide has increased exponentially since the Food and Drug Administration approval of the WATCHMAN (Boston Scientific) device in 2015. The Society for Cardiovascular Angiography & Interventions (SCAI) has previously published statements in 2015 and 2016 providing societal overview of the technology and institutional and operator requirements for LAAC. Since then, results from several important clinical trials and registries have been published, technical expertise and clinical practice have matured over time, and the device and imaging technologies have evolved. Therefore, SCAI prioritized the development of an updated consensus statement to provide recommendations on contemporary, evidence-based best practices for transcatheter LAAC focusing on endovascular devices.

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 categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.413
Bibliometrics0.0000.001
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 head0.085
GPT teacher head0.354
Teacher spread0.270 · 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.

Study designNot applicable
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

Citations24
Published2023
Admission routes1
Has abstractyes

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