When to Say NO to Catheter Ablation of VT/PVCs ?-When to Say NO to Catheter Ablation of VT/PVCs ?

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Video Summary

The Heart Rhythm Society's 46th annual meeting in San Diego, Heart Rhythm 2025, featured several insightful presentations focusing on the management of ventricular premature complexes (PVCs) and ventricular tachycardia (VT). Dr. Peter Pajko from the Czech Republic emphasized when not to pursue ablation for patients with frequent PVCs, highlighting cases like Anderson-Tuttle syndrome and mapping challenges. He noted that although ablation is effective, genetic conditions should prompt reconsideration of treatment strategies.<br /><br />Dr. Konstantinos Tsiontis from Mayo Clinic discussed scenarios where escalating ablation isn't ideal for VT management, especially in high-risk patients. He stressed the importance of assessing each patient's risk and potential to benefit, considering alternatives like antiarrhythmic drugs or advanced therapies (e.g., transplant) if appropriate.<br /><br />Dr. Andrew Epstein from the University of Pennsylvania elaborated on the role of antiarrhythmic drugs, noting that they are effective, noninvasive, and consistent with guidelines. He emphasized shared decision-making with patients and pointed out that Stepwise treatment approaches allow ablation to be a later consideration.<br /><br />Dr. Melissa Robinson from the Providence Heart Institute tackled the topic of VT as a terminal heart failure event and discussed predicting tools like deep learning and CMR imaging to identify at-risk patients. She highlighted that leveraging advanced imaging and data could improve our understanding of VT development in heart failure patients.<br /><br />Overall, the meeting underscored the need for personalized treatment approaches in managing heart rhythm disorders, taking into account individual patient profiles, risk factors, and preferences.

Keywords

Heart Rhythm Society

ventricular premature complexes

ventricular tachycardia

ablation

antiarrhythmic drugs

personalized treatment

deep learning

CMR imaging

heart failure

risk assessment