Graham Lohrmann1, Rachel Kaplan1, Paul D Ziegler2, João Monteiro2, Rod Passman1,3,4. 1. Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. 2. Medtronic Inc, Minneapolis, Minnesota, USA. 3. Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Chicago, Illinois, USA. 4. Northwestern University Center for Arrhythmia Research, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Abstract
INTRODUCTION: Ablation for atrial fibrillation (AF) has emerged as an effective method of rhythm control. This exploratory analysis aimed to determine how various measures of recurrence would influence the definition of treatment success. METHODS: Using an electronic health record data set from January 2007 to June 2019 linked with Medtronic cardiac implantable electronic device (CIED) data, patients who underwent a first AF ablation procedure following CIED implantation were identified. Data were analyzed for recurrence of AF stratified by varying definitions of successful ablation. The performance of various simulated external AF monitoring strategies was assessed. RESULTS: A total of 665 patients were analyzed including 248 with paroxysmal AF (mean age: 66.2 ± 9.3 years, 73.0% male) and 417 patients with persistent AF (mean age: 67.3 ± 9.0 years, 73.6% male). Among patients with paroxysmal AF, survival free from recurrence at 1 year ranged from 28.2% to 72.1% (>6 min and >23 h thresholds, respectively) with an overall median percentage of time in AF reduction of 99.6%. Among patients with persistent AF, survival free from recurrence at 1 year ranged from 24.9% to 60.0% (>6 min and 7 consecutive days > 23 h thresholds, respectively) with an overall median percentage of time in AF reduction of 99.3%. A single 7-day monitoring strategy had a sensitivity of less than 50% for detecting AF greater than 6 min in patients with paroxysmal and persistent AF. CONCLUSION: In this real-world data set of AF patients with CIEDs undergoing catheter ablation, treatment success varied substantially with different definitions of minimally required AF duration and is significantly impacted by the method of recurrence detection.
INTRODUCTION: Ablation for atrial fibrillation (AF) has emerged as an effective method of rhythm control. This exploratory analysis aimed to determine how various measures of recurrence would influence the definition of treatment success. METHODS: Using an electronic health record data set from January 2007 to June 2019 linked with Medtronic cardiac implantable electronic device (CIED) data, patients who underwent a first AF ablation procedure following CIED implantation were identified. Data were analyzed for recurrence of AF stratified by varying definitions of successful ablation. The performance of various simulated external AF monitoring strategies was assessed. RESULTS: A total of 665 patients were analyzed including 248 with paroxysmal AF (mean age: 66.2 ± 9.3 years, 73.0% male) and 417 patients with persistent AF (mean age: 67.3 ± 9.0 years, 73.6% male). Among patients with paroxysmal AF, survival free from recurrence at 1 year ranged from 28.2% to 72.1% (>6 min and >23 h thresholds, respectively) with an overall median percentage of time in AF reduction of 99.6%. Among patients with persistent AF, survival free from recurrence at 1 year ranged from 24.9% to 60.0% (>6 min and 7 consecutive days > 23 h thresholds, respectively) with an overall median percentage of time in AF reduction of 99.3%. A single 7-day monitoring strategy had a sensitivity of less than 50% for detecting AF greater than 6 min in patients with paroxysmal and persistent AF. CONCLUSION: In this real-world data set of AFpatients with CIEDs undergoing catheter ablation, treatment success varied substantially with different definitions of minimally required AF duration and is significantly impacted by the method of recurrence detection.
Authors: Graham Lohrmann; Albert Liu; Paul Ziegler; João Monteiro; Nathan Varberg; Rod Passman Journal: J Interv Card Electrophysiol Date: 2022-08-02 Impact factor: 1.759
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Authors: Graham Peigh; Jeremiah Wasserlauf; Kelly Vogel; Rachel M Kaplan; Anna Pfenniger; Daniel Marks; Arjun Mehta; Alexandru B Chicos; Rishi Arora; Susan Kim; Albert Lin; Nishant Verma; Kaustubha D Patil; Bradley P Knight; Rod S Passman Journal: J Cardiovasc Electrophysiol Date: 2021-07-05 Impact factor: 2.942