Background: No studies evaluating in a quantitative manner the effect of pulmonary vein (PV) isolation on the behavior of atrial premature beats have been reported.
Objectives: The purpose of this study was to reveal the behavior of atrial premature beats before and after PV isolation in patients with paroxysmal atrial fibrillation (AF).
Methods: In 108 patients free from AF following PV isolation, both the number of atrial premature beats and their coupling intervals before and following PV isolation were evaluated with periodic 24-hour ambulatory monitoring.
Results: After a successful PV isolation procedure (group 1, n = 78), the number of atrial premature beats significantly decreased with two distinct time courses: an acute reduction on the following day and a subsequent gradual decrease throughout the whole observation period. The mean atrial premature beat coupling interval at baseline was 420 +/- 30 ms, which was significantly prolonged to 560 +/- 100 ms at 3 months after PV isolation (P <.01). Although patients with AF recurrence after PV isolation (group 2, n = 30) had transiently depressed atrial premature beats shortly after the procedure, they recovered to the former level 3 months after PV isolation. Repeat PV isolation targeting the reconnected PVs successfully suppressed these residual atrial premature beats both in their number and the coupling interval in a manner similar to those in group 1.
Conclusion: Successful PV isolation reduced the number of atrial premature beats with both rapid and gradual time courses. The residual atrial premature beats appeared less arrhythmogenic, with longer coupling intervals than those at baseline. AF recurrences after PV isolation were associated with increased atrial premature beat number and shortened coupling interval, which were depressed by reisolation of reconnected PVs.
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http://dx.doi.org/10.1016/j.hrthm.2006.08.023 | DOI Listing |
Ann Med
December 2025
Department of Geriatrics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Tooth extraction is a risk factor for cardiovascular events, particularly in elderly patients. However, no clinical tool has been developed to date to predict the risk of adverse events (AEs) during tooth extraction.
Materials And Methods: We prospectively enrolled 774 elderly patients (aged ≥ 60 years) with cardiovascular disease (CVD) who were scheduled to undergo tooth extraction at the dental surgery department of Shanghai Ninth People's Hospital from January 2021 to July 2022.
World J Cardiol
December 2024
Department of Cardiovascular Medicine, Affiliated Hospital of Inner Mongolia University for Nationalities, Tongliao 028000, Inner Mongolia Autonomous Region, China.
Background: Ventricular arrhythmia is a common type of arrhythmia observed in clinical practice. It is primarily characterized by premature ventricular contractions, ventricular tachycardia, and ventricular fibrillation. Abnormal formation or transmission of cardiac electrical impulses in patients affects cardiac ejection function.
View Article and Find Full Text PDFJAMA Cardiol
December 2024
Section for Cardiac Electrophysiology, Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania, Philadelphia.
Importance: Infrequent intraprocedural premature ventricular complexes (PVCs) limit the efficacy of catheter ablation. Intravascular stimulation of sympathetic nerves via vertebral veins (VVs) has been used to activate cardiac sympathetic tone and may promote PVCs.
Objective: To characterize the ability of direct electrical sympathetic stimulation via VVs to induce PVCs at the time of catheter ablation.
In the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learning.
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