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Record W2907026589 · doi:10.1055/s-0038-1675816

The Non-Vitamin K Antagonist Oral Anticoagulants in Heart Disease: Section V—Special Situations

2018· review· en· W2907026589 on OpenAlexafffund
Raffaele De Caterina, Walter Ageno, Giancarlo Agnelli, Noel Chan, Hans‐Christoph Diener, Elaine M. Hylek, Gary E. Raskob, Deborah Siegal, Freek W.A. Verheugt, Gregory Y.H. Lip, Jeffrey I. Weitz

Bibliographic record

VenueThrombosis and Haemostasis · 2018
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsPopulation Health Research InstituteMcMaster UniversityThrombosis and Atherosclerosis Research Institute
FundersHamilton Health Sciences FoundationNational Institute for Health and Care ResearchMcMaster UniversityHamilton Health SciencesHeart and Stroke Foundation of Canada
KeywordsRivaroxabanApixabanEdoxabanDabigatranMedicineVitamin K antagonistWarfarinDirect thrombin inhibitorIntensive care medicineClinical trialStroke (engine)DosingAnticoagulantAtrial fibrillationPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Non-vitamin K antagonist oral anticoagulants (NOACs) include dabigatran, which inhibits thrombin, and apixaban, betrixaban, edoxaban and rivaroxaban, which inhibit factor Xa. In large clinical trials comparing the NOACs with the vitamin K antagonist (VKA) warfarin, dabigatran, apixaban, rivaroxaban and edoxaban were at least as effective for stroke prevention in atrial fibrillation and for treatment of venous thromboembolism, but were associated with less intracranial bleeding. In addition, the NOACs are more convenient to administer than VKAs because they can be given in fixed doses without routine coagulation monitoring. Consequently, the NOACs are now replacing VKAs for these indications, and their use is increasing. Although, as a class, the NOACs have a favourable benefit-risk profile compared with VKAs, choosing among them is complicated because they have not been compared in head-to-head trials. Therefore, selection depends on the results of the individual trials, renal function, the potential for drug-drug interactions and preference for once- or twice-daily dosing. In addition, several 'special situations' were not adequately studied in the dedicated clinical trials. For these situations, knowledge of the unique pharmacological features of the various NOACs and judicious cross-trial comparison can help inform prescription choices. The purpose of this position article is therefore to help clinicians choose the right anticoagulant for the right patient at the right dose by reviewing a variety of special situations not widely studied in clinical trials.

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 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 score0.909
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.193
GPT teacher head0.431
Teacher spread0.238 · 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 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

Citations34
Published2018
Admission routes2
Has abstractyes

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