Key result
VX1 AI software standardizes persistent AF ablation outcomes but shows no benefit over visual control.
Why the study?
Ablating atrial regions with abnormal electrograms during AF is useful, but outcomes remain highly operator- and center-dependent.
Does VX1 artificial intelligence software standardize and maintain acute and long-term outcomes for electrogram-based ablation in patients with persistent atrial fibrillation compared to visual guidance?
Population
85 patients with persistent AF across 8 centers
Comparison
VX1 dispersion-guided ablation across primary vs satellite centers, and vs visually guided ablation controls
Design
Prospective, multicentric, nonrandomized study
Authors
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VX1 AI may support standardized electrogram-guided ablation across centers; leaves open whether it improves outcomes versus visual guidance in randomized trials.
Cohort (n=85)
Yes
Does VX1 artificial intelligence software standardize and maintain acute and long-term outcomes for electrogram-based ablation in patients with persistent atrial fibrillation compared to visual guidance?
p-value: p=>0.2
An AI software algorithm (VX1) for electrogram-guided ablation in persistent AF is feasible and standardizes outcomes across different centers, achieving results comparable to visually-guided ablation by trained operators.
Seitz et al. (2022) conducted a cohort in persistent atrial fibrillation (n=85). VX1 machine learning software algorithm vs. visual dispersion-guided ablation was evaluated on acute and long-term outcomes after ablation (p=>0.2). The VX1 artificial intelligence software for electrogram-based ablation in persistent atrial fibrillation standardized outcomes across centers and showed similar results to a visual control group (p>0.2).
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