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Record W2051904394 · doi:10.1097/hco.0b013e3283540857

Randomized controlled trials of new oral anticoagulants for stroke prevention in atrial fibrillation

2012· review· en· W2051904394 on OpenAlexaff
Aaron Liew, John W. Eikelboom, Martin O’Donnell

Bibliographic record

VenueCurrent Opinion in Cardiology · 2012
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster University
FundersPfizer
KeywordsMedicineApixabanAtrial fibrillationRivaroxabanDabigatranWarfarinRandomized controlled trialStroke (engine)PopulationInternal medicineIntensive care medicineCardiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The prevalence of atrial fibrillation is increasing because of an aging population. Vitamin K antagonists have been the standard therapy for stroke prevention in atrial fibrillation but are underutilized and often poorly managed because of their inherent limitations. This study critically reviews the recently completed phase 3 randomized controlled trials of new oral anticoagulants (OACs) for stroke prevention in patients with nonvalvular atrial fibrillation: RE-LY (dabigatran), AVERROES (apixaban), ARISTOTLE (apixaban) and ROCKET-AF (rivaroxaban). RECENT FINDINGS: On the basis of their favorable pharmacological characteristics and excellent efficacy and safety profile as demonstrated by the results of the randomized controlled trials, the new OACs have the potential to replace vitamin K antagonists as the first-line treatment for stroke prevention in atrial fibrillation, with warfarin reserved for patients with contraindications to the new OACs and those unable to afford them. SUMMARY: The new OACs represent a major advance for patients with atrial fibrillation with the potential to reduce morbidity and mortality due to cardioembolic stroke.

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)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.463
GPT teacher head0.527
Teacher spread0.064 · 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 designSystematic review
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

Citations10
Published2012
Admission routes1
Has abstractyes

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