Interpreting Findings with Non-Vitamin K Antagonist Oral Anticoagulants in Atrial Fibrillation: Collective Views on Data from Seminal Studies to Present in Clinical Practice
Bibliographic record
Abstract
Clinical trials show that non-vitamin K antagonist oral anticoagulants (NOACs) have good efficacy-safety profiles relative to warfarin across a broad spectrum of patients with non-valvular atrial fibrillation (NVAF). These findings are currently being confirmed for rivaroxaban through real-world evidence, with results from these studies consistent with results from Phase III randomised controlled trials (RCTs). Of all the NOACs, rivaroxaban currently has the most extensive real-world experience across different data sources (prospective and retrospective registries, database analyses, and prospective studies). Anticoagulant-related bleeding is still a concern amongst clinicians, however awareness of patient characteristics and other factors that can increase bleeding risk can assist in the proactive and effective management of bleeding episodes. Particularly, in atrial fibrillation (AF) patients with renal impairment who have an incrementally higher risk of bleeding and stroke, administration of NOACs versus vitamin K antagonists (VKAs) is beneficial. When dosed appropriately, NOACs such as rivaroxaban are effective in patients with renal impairment and offer an alternative to warfarin, with increased efficacy and decreased risk of critical bleeding events.
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 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 | 0.518 | 0.669 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.009 | 0.012 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".