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Record W2066534687 · doi:10.1093/europace/euu069

Ischaemic stroke prevention in patients with atrial fibrillation and high bleeding risk: opportunities and challenges for percutaneous left atrial appendage occlusion

2014· review· en· W2066534687 on OpenAlexaff
T. Lewalter, Prapa Kanagaratnam, Boris Schmidt, Mårten Rosenqvist, Jens Erik Nielsen‐Kudsk, R. Ibrahim, Bert Albers, A. John Camm

Bibliographic record

VenueEP Europace · 2014
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsAtrial fibrillationLeft atrial appendage occlusionMedicineCardiologyPercutaneousInternal medicineStroke (engine)AppendageOcclusionStroke riskAtrial AppendageIschemic strokeWarfarinIschemiaEngineering

Abstract

fetched live from OpenAlex

Patients with atrial fibrillation (AF) are at an increased risk of ischaemic stroke. The efficacy of stroke prevention with vitamin K antagonists in these patients has been well established. However, associated bleeding risks may offset the therapeutic benefits in patients with risk factors for bleeding. Despite improvements achieved by novel oral anticoagulants, bleeding remains a clinically relevant problem, especially gastrointestinal bleeding. Percutaneous occlusion of the left atrial appendage (LAA) may be considered as an alternative stroke prevention therapy in AF patients with a high bleeding risk. This paper explores patient groups in whom oral anticoagulation may be challenging and percutaneous LAA occlusion (LAAO) has a potentially better risk-benefit balance. The current status of LAAO and future directions are reviewed, and particular challenges for LAA occlusion requiring further clinical data are discussed. This article is a summary of the Third Global Summit on LAA occlusion, 15 March 2013, Barcelona, Spain.

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)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.089
GPT teacher head0.326
Teacher spread0.237 · 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

Citations41
Published2014
Admission routes1
Has abstractyes

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