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Is There a Role for Statins in Atrial Fibrillation?

2009· review· en· W2133486607 on OpenAlexaff
David E. Dawe, Vignendra Ariyarajah, Aliasghar Khadem

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2009
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsMedicineAtrial fibrillationIntensive care medicineHeart RhythmPsychological interventionCardiologyPsychiatry

Abstract

fetched live from OpenAlex

3-Hydroxy-3-methyl-glutaryl-CoA reductase inhibitors (statins) are some of the most commonly prescribed drugs in the world. While lipid modification remains the primary function of statins, there has been increasing interest in its potential pleiotropic effects, particularly as an anti-inflammatory agent in its role as an antiarrhythmic. Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice and carries with it a significant burden in both morbidity and mortality. Treatment for AF currently involves either rate or rhythm control where both have demonstrable associated risks. Rate control necessitates anticoagulation, which can cause life-threatening bleeding, while rhythm control has a poor side-effect profile that may lead to greater mortality and may not completely eliminate the need for anticoagulation. Considering this pressing need for novel therapeutic interventions in AF, this long overdue systematic review explores the potential role of statins in the treatment and prevention of AF. Physicians, especially cardiologists, need to be aware of the host of currently available literature and, more importantly, need to be stimulated to generate discussion and formulate studies that will help debate the issues under the most erudite standards.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.118
GPT teacher head0.467
Teacher spread0.348 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations11
Published2009
Admission routes1
Has abstractyes

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