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How Did We Get Here?: A Historical Review and Critical Analysis of Anticoagulation Therapy Following Mechanical Valve Replacement

2019· review· en· W2990610556 on OpenAlexafffund
S. Macisaac, Iqbal Jaffer, Emilie P. Belley‐Côté, G. McClure, John W. Eikelboom, Richard Whitlock

Bibliographic record

VenueCirculation · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsThrombosis and Atherosclerosis Research InstituteMcMaster UniversityPopulation Health Research Institute
FundersHeart and Stroke Foundation of Canada
KeywordsMedicineAntithromboticMechanical heartVitamin K antagonistGuidelineMechanical valveIntensive care medicineWarfarinvalvular heart diseaseRandomized controlled trialClinical trialSurgeryCardiologyInternal medicineAtrial fibrillation

Abstract

fetched live from OpenAlex

Managing severe valvular heart disease with mechanical valve replacement necessitates lifelong anticoagulation with a vitamin K antagonist. Optimal anticoagulation intensity for patients with mechanical valves remains uncertain; current recommendations are inconsistent across guideline bodies and largely based on expert opinion. In this review, we outline the history of anticoagulation therapy in patients with mechanical heart valves and critically evaluate current antithrombotic guidelines for these patients. We conclude that randomized trials evaluating optimal anticoagulation intensity in patients with mechanical valves are needed, and that future guidelines must better justify antithrombotic treatment recommendations.

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)0.002
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.078
GPT teacher head0.408
Teacher spread0.330 · 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

Citations28
Published2019
Admission routes2
Has abstractyes

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