Applications of cardiac computed tomography in electrophysiology intervention
Bibliographic record
Abstract
Cardiac electrophysiology is an evolving specialty that has seen rapid advances in recent years. Concurrently, there has been much progress in the field of cardiac imaging. Electrophysiologists are increasingly requesting cross-sectional imaging in advance of many procedures. Pulmonary vein isolation and left atrial appendage (LAA) occlusion are now an established treatment options for atrial fibrillation. In patients undergoing pulmonary vein isolation, applications of computed tomography (CT) include evaluating the left atrial and pulmonary venous anatomy, excluding LAA thrombus and assessing for pulmonary vein stenosis. In those undergoing LAA occlusion, CT may be of value in assessing the size, position, and morphology of the LAA as well as for determining correct positioning of the device and evaluating for peri-device leak. Implantable cardiac devices are now commonly used in the management of cardiac failure and cardiac arrhythmias. Applications of CT prior to device implantation include detecting myocardial scar, evaluating for mechanical dyssynchrony as well as visualising the coronary venous anatomy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".