EACVI recommendations on cardiovascular imaging for the detection of embolic sources: endorsed by the Canadian Society of Echocardiography
Bibliographic record
Abstract
Cardioaortic embolism to the brain accounts for approximately 15-30% of ischaemic strokes and is often referred to as 'cardioembolic stroke'. One-quarter of patients have more than one cardiac source of embolism and 15% have significant cerebrovascular atherosclerosis. After a careful work-up, up to 30% of ischaemic strokes remain 'cryptogenic', recently redefined as 'embolic strokes of undetermined source'. The diagnosis of cardioembolic stroke remains difficult because a potential cardiac source of embolism does not establish the stroke mechanism. The role of cardiac imaging-transthoracic echocardiography (TTE), transoesophageal echocardiography (TOE), cardiac computed tomography (CT), and magnetic resonance imaging (MRI)-in the diagnosis of potential cardiac sources of embolism, and for therapeutic guidance, is reviewed in these recommendations. Contrast TTE/TOE is highly accurate for detecting left atrial appendage thrombosis in patients with atrial fibrillation, valvular and prosthesis vegetations and thrombosis, aortic arch atheroma, patent foramen ovale, atrial septal defect, and intracardiac tumours. Both CT and MRI are highly accurate for detecting cavity thrombosis, intracardiac tumours, and valvular prosthesis thrombosis. Thus, CT and cardiac magnetic resonance should be considered in addition to TTE and TOE in the detection of a cardiac source of embolism. We propose a diagnostic algorithm where vascular imaging and contrast TTE/TOE are considered the first-line tool in the search for a cardiac source of embolism. CT and MRI are considered as alternative and complementary tools, and their indications are described on a case-by-case approach.
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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 | 0.016 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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".