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Record W2017709949 · doi:10.1160/th12-03-0209

Management consensus guidance for the use of rivaroxaban – an oral, direct factor Xa inhibitor

2012· review· en· W2017709949 on OpenAlexaff
Reinhold Kreutz, Juan V. Llau, Bo Norrving, Sylvia Haas, Alexander G.G. Turpie

Bibliographic record

VenueThrombosis and Haemostasis · 2012
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University
FundersAllerganBayer HealthCarePfizer
KeywordsRivaroxabanApixabanMedicineDabigatranClinical trialDiscovery and development of direct thrombin inhibitorsDirect thrombin inhibitorIntensive care medicineAtrial fibrillationDeep veinStroke (engine)ThrombosisVenous thrombosisWarfarinSurgeryInternal medicineThrombin

Abstract

fetched live from OpenAlex

A number of novel oral anticoagulants that directly target factor Xa or thrombin have been developed in recent years. Rivaroxaban and apixaban (direct factor Xa inhibitors) and dabigatran etexilate (a direct thrombin inhibitor) have shown considerable promise in large-scale, randomised clinical studies for the management of thromboembolic disorders, and have been approved for clinical use in specific indications. Rivaroxaban is licensed for the prevention of venous thromboembolism in patients undergoing elective hip or knee replacement surgery, the treatment of deep-vein thrombosis and prevention of recurrent venous thromboembolism, and for stroke prevention in patients with non-valvular atrial fibrillation. Based on the clinical trial data for rivaroxaban, feedback on its use in clinical practice and the authors' experience with the use of rivaroxaban, practical guidance for the use of rivaroxaban in special patient populations and specific clinical situations is provided. Although most recommendations are in line with the European summary of product characteristics for the approved indications, additional and, in several areas, different recommendations are given based on review of the literature and the authors' clinical experience.

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)0.001
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 score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
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 head0.348
GPT teacher head0.410
Teacher spread0.062 · 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

Citations167
Published2012
Admission routes1
Has abstractyes

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