New Avenues for Optimal Treatment of Atrial Fibrillation and Stroke Prevention
Bibliographic record
Abstract
One in 3 individuals free of atrial fibrillation (AF) at index age 55 years is estimated to develop AF later in life. AF increases not only the risk of ischemic stroke but also of dementia, even in stroke-free patients. In this review, we address recent advances in the heart-brain interaction with focus on AF. Issues discussed are (1) the timing of direct oral anticoagulants start following an ischemic stroke; (2) the comparison of direct oral anticoagulants versus vitamin K antagonists in early secondary stroke prevention; (3) harms of bridging with heparin before direct oral anticoagulants; (4) importance of appropriate direct oral anticoagulants dosing; (5) screening for AF in high-risk populations, including the role of wearables; (6) left atrial appendage occlusion as an alternative to oral anticoagulation; (7) the role of early rhythm-control therapy; (8) effect of lifestyle interventions on AF; (9) AF as a risk factor for dementia. An interdisciplinary approach seems appropriate to address the complex challenges posed by AF.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".