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Record W1975897275 · doi:10.1182/blood-2011-10-378950

How I treat with anticoagulants in 2012: new and old anticoagulants, and when and how to switch

2012· review· en· W1975897275 on OpenAlexaff
Sam Schulman, Mark Crowther

Bibliographic record

VenueBlood · 2012
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsRivaroxabanDabigatranMedicineWarfarinIntensive care medicineDrugAnticoagulantPharmacologySurgeryAtrial fibrillationInternal medicine

Abstract

fetched live from OpenAlex

Two novel oral anticoagulants, dabigatran and rivaroxaban, have recently been approved. They differ in many ways from warfarin, including rapid onset of action, shorter half-life, fewer drug-drug interactions, lack of need for monitoring, and no need for titration or dose adjustments. These novel agents represent a landmark shift in anticoagulant care; however, many aspects of their use will be unfamiliar to practicing clinicians, despite the imminent widespread use of these agents in the community. The management of these anticoagulants when transitioning from or back to warfarin, around surgery or in case of major hemorrhage, requires knowledge of their pharmacokinetics and mechanism of action. Unfortunately, there is a limited evidence base to inform decisions around management of these agents. We present our practice in these settings supported, where available, with literature evidence.

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)0.006
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.110
GPT teacher head0.330
Teacher spread0.220 · 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

Citations247
Published2012
Admission routes1
Has abstractyes

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