Spotlight on unmet needs in stroke prevention: The PIONEER AF-PCI, NAVIGATE ESUS and GALILEO trials
Bibliographic record
Abstract
Atrial fibrillation (AF) is a major healthcare concern, being associated with an estimated five-fold risk of ischaemic stroke. In patients with AF, anticoagulants reduce stroke risk to a greater extent than acetylsalicylic acid (ASA) or dual antiplatelet therapy (DAPT) with ASA plus clopidogrel. Non-vitamin K antagonist oral anticoagulants (NOACs) are now a widely-accepted therapeutic option for stroke prevention in non-valvular AF (NVAF). There are particular patient types with NVAF for whom treatment challenges remain, owing to sparse clinical data, their high-risk nature or a need to harmonise anticoagulant and antiplatelet regimens if co-administered. This article focuses on three randomised controlled trials (RCTs) that are investigating the utility of rivaroxaban, a direct, oral, factor Xa inhibitor, in additional areas of stroke prevention where data for anticoagulants are lacking: oPen-label, randomized, controlled, multicentre study explorIng twO treatmeNt stratEgiEs of Rivaroxaban and a dose-adjusted oral vitamin K antagonist treatment (PIONEER AF-PCI); New Approach riVaroxoban Inhibition of factor Xa in a Global trial vs Aspirin to prevenT Embolism in Embolic Stroke of Undetermined Source (NAVIGATE ESUS); and Global study comparing a rivAroxaban-based antithrombotic strategy to an antipLatelet-based strategy after transcatheter aortIc vaLve rEplacement to Optimize clinical outcomes (GALILEO). Data from these studies present collaborative efforts to build upon existing registrational Phase III data for rivaroxaban, driving the need for effective and safe treatment of a wider range of patients for stroke prevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.064 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".