Embolic Stroke of Undetermined Source
Bibliographic record
Abstract
Embolic strokes of undetermined source (ESUS) represent 9%-25% of all ischemic strokes. Based on the suspicion that a large proportion of cardioembolic sources remain undetected among embolic stroke of undetermined source patients, it has been hypothesized that a universal approach of anticoagulation would be better than aspirin for preventing recurrent strokes. However, 4 randomized controlled trials (RCTs), with different degrees of patient selection, failed to confirm this hypothesis. In parallel, several RCTs consistently demonstrated that prolonged cardiac monitoring increased atrial fibrillation detection and anticoagulation initiation compared with usual care in patients with ESUS, and later in individuals with ischemic stroke of known cause (e.g., large or small vessel disease). However, none of these trials or subsequent meta-analyses of all available RCTs have shown a reduction in stroke recurrence associated with the use of prolonged cardiac monitoring. In this article, we review the clinical and research implications of recent RCTs of antithrombotic therapy in patients with ESUS and in high-risk populations with and without stroke, with device-detected asymptomatic atrial fibrillation.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".