EACVI/EHRA Expert Consensus Document on the role of multi-modality imaging for the evaluation of patients with atrial fibrillation
Bibliographic record
Abstract
Atrial fibrillation (AF) is the commonest cardiac rhythm disorder. Evaluation of patients with AF requires an electrocardiogram, but imaging techniques should be considered for defining management and driving treatment. The present document is an expert consensus from the European Association of Cardiovascular Imaging (EACVI) and the European Heart Rhythm Association. The clinical value of echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), and nuclear imaging in AF patients are challenged. Left atrial (LA) volume and strain in echocardiography as well as assessment of LA fibrosis in CMR are discussed. The value of CT, especially in planning interventions, is highlighted. Fourteen consensus statements have been reached. These may serve as a guide for both imagers and electrophysiologists for best selecting the imaging technique and for best interpreting its results in AF patients.
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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 | 0.036 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".