Preventive Ventricular Tachycardia Ablation in Patients with Ischaemic Cardiomyopathy: Meta-analysis of Randomised Trials
Bibliographic record
Abstract
Catheter ablation of ventricular tachycardia (VT) aims to treat the underlying arrhythmia substrate to prevent ICD therapies. The aim of this meta-analysis was to assess the safety and efficacy of VT ablation prior to or at the time of secondary prevention ICD implantation in patients with coronary artery disease, as compared with deferred VT ablation. Based on a systematic literature search, three randomised trials were considered eligible for inclusion in this analysis, and data on the number of patients with appropriate ICD shocks, appropriate ICD therapy, arrhythmic storm, death and major complications were extracted from each study. On pooled analysis, there was a significant reduction of appropriate ICD shocks (OR 2.58; 95% CI [1.54-4.34]; p<0.001) and appropriate ICD therapies (OR 2.04; 95% CI [1.15-3.61]; p=0.015) in patients undergoing VT ablation at the time of ICD implantation without significant differences with respect to complications (OR 1.39; 95% CI [0.43-4.51]; p=0.581). Mortality did not differ between both groups (OR 1.30; 95% CI [0.60-2.45]; p=0.422). Preventive catheter ablation of VT in patients with coronary heart disease at the time of secondary prevention ICD implantation results in a significant reduction of appropriate ICD shocks and any appropriate ICD therapy compared with patients without or with deferred VT ablation. No significant difference with respect to complications or mortality was observed between both treatment strategies.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.040 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".