Atrial Fibrillation Detection and Load: Knowledge Gaps Related to Stroke Prevention
Bibliographic record
Abstract
Atrial fibrillation is a major cause of ischemic stroke. Technological advances now support prolonged cardiac rhythm monitoring using either surface electrodes or insertable cardiac monitors. Four major randomized controlled trials show that prolonged cardiac monitoring detects subclinical paroxysmal atrial fibrillation in 9% to 16% of patients with ischemic stroke, including in patients with potential alternative causes such as large artery disease or small vessel occlusion; however, the optimal monitoring strategy, including the target patient population and the monitoring device (whether to use an event monitor, insertable cardiac monitor, or stepped approach) has not been well defined. Furthermore, the clinical significance of very short duration paroxysmal atrial fibrillation remains controversial. The relevance of the duration of monitoring, burden of device-detected atrial fibrillation, and its proximity to the acute ischemic stroke will require more research to define the most effective methods for stroke prevention in this patient population.
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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 | 0.026 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".