Choosing a particular oral anticoagulant and dose for stroke prevention in individual patients with non-valvular atrial fibrillation: part 1
Bibliographic record
Abstract
Patients with atrial fibrillation (AF) have a high risk of stroke and mortality, which can be considerably reduced by oral anticoagulants (OAC). Recently, four non-vitamin-K oral anticoagulants (NOACs) were compared with warfarin in large randomized trials for the prevention of stroke and systemic embolism. Today's clinician is faced with the difficult task of selecting a suitable OAC for a patient with a particular clinical profile or a particular pattern of risk factors and concomitant diseases. We reviewed analyses of subgroups of patients from trials of vitamin K antagonists vs. NOACs for stroke prevention in AF with the aim to identify patient groups who might benefit from a particular OAC more than from another. In the first of a two-part review, we discuss the choice of NOAC for stroke prevention in the following subgroups of patients with AF: (i) stable coronary artery disease or peripheral artery disease, including percutaneous coronary intervention with stenting and triple therapy; (ii) cardioversion, ablation and anti-arrhythmic drug therapy; (iii) mechanical valves and rheumatic valve disease, (iv) patients with time in therapeutic range of >70% on warfarin; (v) patients with a single stroke risk factor (CHA2DS2VASc score of 1 in males, 2 in females); and (vi) patients with a single first episode of paroxysmal AF. Although there are no major differences in terms of efficacy and safety between the NOACs for some clinical scenarios, in others we are able to suggest that particular drugs and/or doses be prioritized for anticoagulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".