Optimum Patient's Selection for Atrial Fibrillation Ablation Using Echocardiography

Catheter ablation (CA) has become a validated technique for treating patients with symptomatic or paroxysmal atrial fibrillation (AF), as recommended by the latest 2024 European society of cardiology (ESC) guidelines, class II level A. The procedure is also recommended for patients with persistent AF without major risk factors for AF recurrence, as an alternative to antiarrhythmic medications class I or III. However, CA carries the risk of AF recurrence in 30-35% of patients, sometimes after the procedure. Multiple factors impact the onset, maintenance, and recurrence of AF after CA, including clinical, biohumoral, echocardiographic, genetic, and lifestyle factors. Beyond traditional predictors, emerging factors such as obstructive sleep apnea syndrome, chronic renal failure, chronic lung disease, physical activity patterns, gut microbiota composition, and epicardial fat thickness significantly influence outcomes. Therefore, optimizing patient's selection for CA is an important strategy to minimize the risk of AF recurrence. Many echocardiographic parameters emerged as predictors of AF recurrence post-CA, but none stood out as a potential single factor. These factors include traditional markers such as left atrial size by 2D echocardiography, LV ejection fraction, LV diastolic function parameters as well as myocardial deformation addressed by the recently developed speckle tracking analysis. Additionally, the duration and type of AF represent fundamental risk factors, with longstanding persistent AF showing significantly higher recurrence rates compared to paroxysmal forms. Novel biomarkers including MR-proANP, caspase-8, hsa-miR-206, and neurotrophin-3 show promise in enhancing risk prediction capabilities. The aim of this review is to explore the most relevant echocardiographic parameters, including myocardial deformation, that could accurately predict recurrence of AF after CA, while also examining the role of emerging clinical and biochemical predictors in comprehensive patient selection strategies.