Key result
An 'in silico' biophysical model of atrial fibrillation predicted 'in vivo' surgical ablation outcomes, with simulated conversion to sinus rhythm correlating strongly with clinical rates (r2=0.973).
Why the study?
Does an 'in silico' biophysical model of atrial fibrillation accurately predict the fraction of conversions to sinus rhythm compared to 'in vivo' surgical ablation?
Population
46 consecutive adult patients with symptomatic permanent drug refractory atrial fibrillation undergoing…
Comparison
'In silico' biophysical modeling of incomplete… vs 'In vivo' surgical ablation and historical…
Authors
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May inform ablation strategy selection in AF surgery; leaves open prospective confirmation of clinical benefit.
Observational (n=46)
Does an 'in silico' biophysical model of atrial fibrillation accurately predict the fraction of conversions to sinus rhythm compared to 'in vivo' surgical ablation?
Effect estimate: r2=0.973
Absolute Event Rate: 88% vs 92%
p-value: p=ns
An 'in silico' biophysical model of atrial fibrillation accurately predicts conversion rates to sinus rhythm following surgical ablation, providing a non-invasive tool for optimizing ablation patterns.
Ruchat et al. (2007) conducted an observational in symptomatic permanent drug refractory atrial fibrillation (n=46). In silico biophysical model of atrial fibrillation vs. In vivo surgical ablation was evaluated on Fraction of conversions to sinus rhythm (SR) (r2=0.973, p=ns). An 'in silico' biophysical model of atrial fibrillation predicted 'in vivo' surgical ablation outcomes, with simulated conversion to sinus rhythm correlating strongly with clinical rates (r2=0.973).
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