Embolic strokes of undetermined source: a clinical consensus statement of the ESC Council on Stroke, the European Association of Cardiovascular Imaging and the European Heart Rhythm Association of the ESC
Bibliographic record
Abstract
One in six ischaemic stroke patients has an embolic stroke of undetermined source (ESUS), defined as a stroke with unclear aetiology despite recommended diagnostic evaluation. The overall cardiovascular risk of ESUS is high and it is important to optimize strategies to prevent recurrent stroke and other cardiovascular events. The aim of clinicians when confronted with a patient not only with ESUS but also with any other medical condition of unclear aetiology is to identify the actual cause amongst a list of potential differential diagnoses, in order to optimize secondary prevention. However, specifically in ESUS, this may be challenging as multiple potential thromboembolic sources frequently coexist. Also, it can be delusively reassuring because despite the implementation of specific treatments for the individual pathology presumed to be the actual thromboembolic source, patients can still be vulnerable to stroke and other cardiovascular events caused by other pathologies already identified during the index diagnostic evaluation but whose thromboembolic potential was underestimated. Therefore, rather than trying to presume which particular mechanism is the actual embolic source in an ESUS patient, it is important to assess the overall thromboembolic risk of the patient through synthesis of the individual risks linked to all pathologies present, regardless if presumed causally associated or not. In this paper, a multi-disciplinary panel of clinicians/researchers from various backgrounds of expertise and specialties (cardiology, internal medicine, neurology, radiology and vascular surgery) proposes a comprehensive multi-dimensional assessment of the overall thromboembolic risk in ESUS patients through the composition of individual risks associated with all prevalent pathologies.
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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 | 0.037 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".