5203Ablation of scar-related ventricular tachycardia: paced electrogram feature analysis (PEFA) is a novel and effective substrate based strategy
Bibliographic record
Abstract
Abstract Background Ablation of scar related ventricular tachycardia (VT) has been shown to be superior to escalation of drug therapy. However, the incremental benefit remains modest, with 42% experiencing recurrent shocks and 64% appropriate anti-tachycardia pacing (ATP) in the VANISH study. Improved ablation strategies are needed. Paced electrogram feature analysis (PEFA) is a novel substrate based ablation technique. Purpose To investigate the effectiveness of the PEFA based VT ablation technique. Methods A single centre, prospective study. Consecutive cases of scar related VT that had an implantable cardiac defibrillator (ICD) and no prior ablations were recruited. Close coupled pacing was performed at the right ventricular apex and the VT isthmus(es) identified on high density mapping catheters by increased electrogram (EGM) duration and latency. A algorithm was developed to identify the latest EGM component after the S2 pacing artefact,. This millisecond value was displayed on the geometry as a colour (PEFA map) (St Jude Ensite Precision Electroanatomic Mapping). PEFA identified VT isthmus sites were targeted for ablation (Figure 1). Follow up ICD interrogation data was utilized to assess for VT recurrence. Results A total of 20 patients were recruited. These comprised ischaemic cardiomyopathy (CM) (17/20), dilated CM (2/20), and arrhythmogenic CM (1/20), male (18/20), and endocardial only approach (19/20). Mean age was 64.3±11.3 years, ejection fraction 24.4% ± 14.4, and ablation time was 1989.9±1078.1 seconds. Non-inducibility was demonstrated at the end of the case in 18/20. A class I or III anti-arrhythmic drug was continued in 50%. VT recurred in three cases (Day 28,30,55). One death occurred following a stroke on day 181. Mean follow up was 437.5±231.7 days. Figure 1 Conclusion This is the largest study to date on PEFA based VT ablation, the first to include non-ischaemic aetiologies, and reports a longer mean follow up. A high proportion of cases were non-inducible, and low VT recurrence rates were observed. PEFA appears to be a promising tool to guide VT ablation targets. Acknowledgement/Funding This research was funded in part by the Canadian Institute for Health Research (139080) and a grant from St. Jude Medical.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".