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Record W2553577692 · doi:10.1097/hco.0000000000000365

Oral anticoagulation for stroke prevention amongst atrial fibrillation patients with valvular heart disease

2016· review· en· W2553577692 on OpenAlexaff
Andrew C.T. Ha, Atul Verma, Subodh Verma

Bibliographic record

VenueCurrent Opinion in Cardiology · 2016
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsSouthlake Regional Health CenterUniversity of TorontoUniversity Health NetworkSt. Michael's HospitalToronto General Hospital
Fundersnot available
KeywordsMedicineAtrial fibrillationStroke (engine)valvular heart diseaseCardiologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The majority of evidence on the safety and efficacy of oral anticoagulation for stroke prevention amongst patients with atrial fibrillation is derived from those without significant valvular heart disease. This article will review current knowledge, areas of uncertainty and controversy, and ongoing research on oral anticoagulation for stroke prevention amongst patients with valvular heart disease. RECENT FINDINGS: The rates of stroke, systemic embolism, and major bleeding were similar for patients with and without significant native valvular disease when treated with direct oral anticoagulants (DOACs) or vitamin K antagonists. There are very limited prospective data on the safety and efficacy of DOAC use for patients with bioprosthetic valves or rheumatic mitral stenosis. SUMMARY: Atrial fibrillation patients with concomitant valvulopathies constitute a group with high thromboembolic risk and should be treated with oral anticoagulation. There is good supportive evidence that DOAC is well tolerated and effective in preventing thromboembolism amongst patients with native valvular disease. Further research is underway to better define the risks and benefits of DOAC use among patients with bioprosthetic valves or rheumatic mitral stenosis in preventing thromboembolic events. Until then, vitamin K antagonists remain the oral anticoagulant of choice for these patient subsets.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.156
GPT teacher head0.437
Teacher spread0.281 · 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.

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

Citations9
Published2016
Admission routes1
Has abstractyes

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