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Record W4366490436 · doi:10.1016/j.cjco.2023.03.016

The Canadian WATCHMAN Registry for Percutaneous Left Atrial Appendage Closure

2023· article· en· W4366490436 on OpenAlexaffabout
Jacqueline Saw, Taku Inohara, Thomas Gilhofer, Naomi Uchida, Colin D. Pearce, Payam Dehghani, Malek Kass, Réda Ibrahim, Carlos A. Morillo, Stephan Wardell, Jean‐Michel Paradis, Gilles O’Hara

Bibliographic record

VenueCJC Open · 2023
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMontreal Heart InstituteUniversity of CalgaryGenome PrairieSt. Boniface HospitalRoyal University HospitalInstitut Universitaire de Cardiologie et de Pneumologie de QuébecLibin Cardiovascular Institute of AlbertaRegina General HospitalVancouver General Hospital
FundersSunovionNational Institutes of HealthBoston Scientific CorporationEdwards LifesciencesAstraZenecaServierPfizer
KeywordsAppendagePercutaneousMedicineCardiologyAtrial fibrillationInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Background: Access to left atrial appendage closure (LAAC) in Canada is limited, due to funding restrictions. This work aimed to assess Canadian clinical practice on patient selection, postprocedural antithrombotic therapy, and safety and/or efficacy with WATCHMAN device implantation. Methods: -VASc score. Results: -VASc score (6.0% expected vs 1.1% observed). Device-related thrombus was detected in 1.8%. Conclusions: The majority of Canadian patients who underwent LAAC had oral anticoagulation contraindication due to prior bleeding, and most were safely treated with antiplatelet therapy post-LAAC, with a low device-related thrombus incidence. Long-term follow-up demonstrated that LAAC achieved a significant reduction in ischemic stroke rate.

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)0.004
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 score0.991
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.071
GPT teacher head0.363
Teacher spread0.292 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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Same venueCJC OpenSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207