Ventricular tachycardia ablation in arrhythmogenic right ventricular cardiomyopathy patients with TMEM43 gene mutations
Bibliographic record
Abstract
INTRODUCTION: Catheter ablation of VT in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) is often challenging, frequently requiring multiple or epicardial ablation procedures; TMEM43 gene mutations typically cause aggressive disease. We sought to compare VT ablation outcomes for ARVC patients with and without TMEM43 mutations. METHODS: Patients with prior ablation for ARVC-related VT were reviewed. Demographic, procedural, and follow-up data were reviewed retrospectively. Patients with confirmed TMEM43 gene mutations were compared to those with other known mutations or who had no known mutations. RESULTS: Thirteen patients (10 male, mean age 49 ± 14 years) underwent 29 ablation procedures (median 2 procedures/patient, range 1-6) with a median of 4 targeted VTs/patient (range 1-9). They were followed for a mean duration of 7.3 ± 4.2 years. Gene mutations included TMEM43 (n = 5), PKP2 (n = 2), DSG2 (n = 2), unidentifiable (n = 4). TMEM patients showed more biventricular involvement compared to non-TMEM patients (80% vs. 12.5%, P = 0.032), more inducible VTs during their ablation procedures (mean VTs/patient: 5.8 ± 3 vs. 2.6 ± 1, P = 0.021). Acute and long-term procedural outcomes did not show a significant difference between the two groups, however TMEM patients had worse composite endpoint of death or transplantation (60% vs. 0, P = 0.035; log-rank P = 0.013). CONCLUSIONS: TMEM43 mutation patients were more likely to have biventricular arrhythmogenic substrate and more inducible VTs at EP study. Despite comparable acute VT ablation outcomes, long-term prognosis is unfavorable.
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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 | 0.002 |
| 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".