Recent advances in ablation of ventricular tachycardia associated with structural heart disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Ablation of ventricular tachycardia in structural heart disease has evolved to include techniques to ablate the myocardial substrate in sinus rhythm for ventricular tachycardias that are noninducible or hemodynamically unstable. The intricacies of the complex functional and fixed components of the myocardial scar involved in the arrhythmic mechanisms require careful consideration in identifying targets for substrate ablation identified in sinus rhythm. RECENT FINDINGS: The substrate ablation approach referred to as 'scar homogenization' aims to thoroughly abolish any abnormal electrical activity inside the scar. However, this extensive approach may target bystander abnormal activity that is not necessarily related to arrhythmias. Recently, different substrate ablation strategies have been developed to more selectively target areas of the scar responsible for ventricular tachycardia. New technologies have also been introduced to provide offline analysis of the electroanatomical substrate, and to improve high-density mapping of the myocardial scar. SUMMARY: Recent advances have improved the ability to ablate ventricular tachycardia using techniques that allow targeting the responsible myocardial substrate while in sinus rhythm. Further research using higher-density mapping with more sophisticated online and offline analysis will aid in the assessment of the complex arrhythmogenicity of the scar and improve efficacy of ventricular tachycardia ablation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".