The role of catheter ablation for ventricular tachycardia in patients with ischemic heart disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Catheter ablation has evolved remarkably over the last 2 decades, bringing nonpharmacologic therapy to complex arrhythmias like atrial fibrillation and scar-related ventricular tachycardia. As our therapeutic options have increased for patients with ventricular tachycardia, choosing the right therapy for the right patient has become more complex. Ablation carries acute and perhaps longer-term procedural risk and variable success, whereas drug therapy likewise is limited by both side-effects and efficacy. RECENT FINDINGS: Early randomized trials of catheter ablation for ventricular tachycardia and multicenter experiences have recently been published, and further studies are underway to define the appropriate application of this therapy. Randomized trials have demonstrated that catheter ablation can reduce ventricular tachycardia episodes with relatively low risk. Multicenter experience has demonstrated a moderate risk of serious procedural adverse events in this very sick population, but ablation has never been compared directly with antiarrhythmic drug therapy. SUMMARY: There is still little evidence to clarify the relative merits of antiarrhythmic drug therapy in comparison with ablation. The optimal role of either therapy will remain uncertain until the completion of trials currently in progress. Until further evidence is available, most clinicians advocate first-line antiarrhythmic drug therapy, and reserve catheter ablation for when this fails or is not tolerated.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".