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Record W2148721718 · doi:10.1586/14779072.3.4.619

Nonpharmacologic stroke prevention in atrial fibrillation

2005· review· en· W2148721718 on OpenAlexaff
Orhan Önalan, Ilan Lashevsky, Adel Khalifa Hamad, Eugene Crystal

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2005
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsWomen's College HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineAtrial fibrillationStroke (engine)CardiologyPercutaneousCatheter ablationInternal medicineThromboembolic strokeIntensive care medicine

Abstract

fetched live from OpenAlex

Atrial fibrillation is associated with significant mortality and morbidity. The burden of morbidity in atrial fibrillation is mostly due to stroke, one of the major causes of death and the leading cause of long-term disability. Although highly effective in prevention of thromboembolic stroke, several factors limit utilization of chronic oral anticoagulation therapy. Eradication of atrial fibrillation and restoration of effective atrial contraction by surgical methods, or recently, by percutaneous catheter ablation methods, are two attractive approaches for stroke prophylaxis. Surgical exclusion of the left atrial appendage has generated considerable interest in the past decades and it is now performed routinely during mitral valve surgery in many centers. Recently, minimally invasive and percutaneous methods for the exclusion of left atrial appendage have been introduced. Currently, these approaches are being evaluated in ongoing trials. This review will discuss the current status of nonpharmacologic methods in the prevention of stroke in atrial fibrillation.

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)0.001
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.120
GPT teacher head0.442
Teacher spread0.322 · 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

Citations54
Published2005
Admission routes1
Has abstractyes

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