Journal of Arrhythmia最新文献

ATTR amyloidosis patient with initial atrial capture failure showed delayed threshold improvement over time. Stable current of injury and impedance guided expectant management, avoiding unnecessary device repositioning while achieving successful outcomes.

This case discusses the differential diagnosis of the double transition sign during bipolar threshold testing following conduction system pacing and delves into the details of electrophysiologic parameters of successful left bundle capture.

In recent years, the number of cases diagnosed with wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM) has been increasing. However, ATTRwt-CM frequently coexists with atrial fibrillation (AF), atrial flutter (AFL), and atrial tachycardia (AT), often necessitating management for arrhythmias. Additionally, ventricular arrhythmias sometimes occur, or conduction disturbances often develop, requiring management for bradycardia, frequently needing device therapy such as pacemakers, implantable cardioverter defibrillators (ICDs), or cardiac resynchronization therapy defibrillators. Therefore, for arrhythmia specialists, who primarily focus on non-pharmacological treatments, arrhythmias associated with ATTRwt-CM are unavoidable encounters, and becoming proficient in their management is increasingly important and considered essential. However, we sometimes encounter AF, AFL, or AT that are extremely difficult to treat with catheter ablation, and there are many situations to struggle with: how to manage each arrhythmia and whether catheter ablation should be performed at all. Furthermore, while the usefulness of ICDs for primary prevention of sudden cardiac death remains a subject of debate, we occasionally encounter patients with ventricular arrhythmias in fact. This review primarily addresses and focuses on catheter ablation therapy for atrial arrhythmias associated with ATTRwt-CM, as well as device therapy for bradyarrhythmias and ventricular arrhythmias, aiming to provide insights for treatment planning in the future as a total management approach to arrhythmia in ATTRwt-CM patients, especially for arrhythmia specialists.

Background: Although artificial intelligence (AI) has been developed to identify patients with paroxysmal atrial fibrillation (PAF) during sinus rhythm, information on its variability remains limited. We evaluated the reproducibility and effect of recording condition on the estimation of AF risk using an electrocardiography (ECG) machine equipped with an AI-based program.

Methods: We extracted two ECG data from a single ECG test in 149 patients to evaluate reproducibility within 4 min. We also recorded ECG signals under 12 conditions (standard, two conditions shifting precordial electrodes, five conditions moving limb electrodes to the torso, three conditions contaminating noise, and reproducibility over 15 min) in 30 participants to evaluate changes from the standard. The results of the AF risk estimation are expressed at four levels.

Results: The rate of participants within one level of error was 95% for reproducibility within 4 min and 87% for reproducibility over 15 min. Shifting the precordial electrodes upward or downward and replacing the left leg electrode with the torso electrode frequently caused a two- or three-level change. In clinical information, increased brain natriuretic peptide tended to increase the variability.

Conclusions: The AF risk estimated by the AI-based program exhibited temporal variability. Shifting the precordial electrodes influenced AI-based AF risk estimation.

A. Yılmaz, “Comment on “The Crucial Role of Physical Activity Index in Predicting the Incidence of Pacemaker Syndrome”,” Journal of Arrhythmia 42, no. 1 (2026): e70261, https://doi.org/10.1002/joa3.70261.

In the published article, References 1, 2, 3, 4, and 6 contained errors. The corrected references are provided below.

The corrected references are as follows:

Citation 1: G. A. Lamas, E. J. Orav, B. S. Stambler, K. A. Ellenbogen, E. B. Sgarbossa, S. K. S. Huang, and B. L. Wilkoff, “Quality of Life and Clinical Outcomes in Elderly Patients Treated With Ventricular Pacing as Compared With Dual-Chamber Pacing,” New England Journal of Medicine 338, no. 16 (1998): 1097–1104.

Citation 2: S. J. Connolly, C. R. Kerr, M. Gent, R. S. Roberts, S. Yusuf, A. M. Gillis, and D. M. Newman, “Effects of Physiologic Pacing Versus Ventricular Pacing on the Risk of Stroke and Death due to Cardiovascular Causes,” New England Journal of Medicine 342, no. 19 (2000): 1385–1391.

Citation 3: M. S. Link, A. S. Hellkamp, N. M. Estes, E. J. Orav, K. A. Ellenbogen, B. Ibrahim, and MOST Study Investigators, “High Incidence of Pacemaker Syndrome in Patients With Sinus Node Dysfunction Treated With Ventricular-Based Pacing in the Mode Selection Trial (MOST),” Journal of the American College of Cardiology 43, no. 11 (2004): 2066–2071.

Citation 4: M. Glikson, J. C. Nielsen, M. B. Kronborg, Y. Michowitz, A. Auricchio, I. M. Barbash, and K. K. Witte, “2021 ESC Guidelines on Cardiac Pacing and Cardiac Resynchronization Therapy: Developed by the Task Force on Cardiac Pacing and Cardiac Resynchronization Therapy of the European Society of Cardiology (ESC) With the Special Contribution of the European Heart Rhythm Association (EHRA),” EP Europace 24, no. 1 (2022): 71–164.

Citation 6: V. Somma, F. J. Ha, S. Palmer, U. Mohamed, and S. Agarwal, “Pacing-Induced Cardiomyopathy: A Systematic Review and Meta-Analysis of Definition, Prevalence, Risk Factors, and Management,” Heart Rhythm 20, no. 2 (2023): 282–290.

We apologize for this error.