Siontis, Konstantinos C.

Abstract Aims Catheter ablation is an effective treatment for post-infarction ventricular tachycardia (VT). However, some patients may experience a worsened arrhythmia phenotype after ablation. We aimed to determine the prevalence and prognostic impact of arrhythmia exacerbation (AE) after post-infarction VT ablation. Methods and results A total of 1187 consecutive patients (93% men, median age 68 years, median ejection fraction 30%) who underwent post-infarction VT ablation at six centres were included. Arrhythmia exacerbation was defined as post-ablation VT storm or incessant VT in patients without prior similar events. During follow-up (median 717 days), 426 (36%) patients experienced VT recurrence. Events qualifying as AE occurred in 67 patients (6%). Median times to VT recurrence with and without AE were 238 [interquartile range (IQR) 35–640] days and 135 (IQR 22–521) days, respectively (P = 0.25). Almost half of the patients (46%) who experienced AE experienced it within 6 months of the index procedure. Patients with AE had had longer ablation times during the ablation procedures compared to the rest of the patients (median 42 vs. 34 min, P = 0.02). Among patients with VT recurrence, the risk of death or heart transplantation was significantly higher in patients with than without AE (hazard ratio 1.99, 95% CI 1.28–3.10; P = 0.002) after adjusting for age, gender, ejection fraction, cardiac resynchronization therapy, post-ablation non-inducibility, and post-ablation amiodarone use. Conclusion Arrhythmia exacerbation after ablation of infarct-related VT is infrequent but is independently associated with an adverse long-term outcome among patients who experience a VT recurrence. The mechanisms and mitigation strategies of AE after catheter ablation require further investigation.

Machine learning applications in cardiology have rapidly evolved in the past decade. With the availability of machine learning tools coupled with vast data sources, the management of atrial fibrillation (AF), a common chronic disease with significant associated morbidity and socioeconomic impact, is undergoing a knowledge and practice transformation in the increasingly complex healthcare environment. Among other advances, deep-learning machine learning methods, including convolutional neural networks, have enabled the development of AF screening pathways using the ubiquitous 12-lead ECG to detect asymptomatic paroxysmal AF in at-risk populations (such as those with cryptogenic stroke), the refinement of AF and stroke prediction schemes through comprehensive digital phenotyping using structured and unstructured data abstraction from the electronic health record or wearable monitoring technologies, and the optimization of treatment strategies, ranging from stroke prophylaxis to monitoring of antiarrhythmic drug (AAD) therapy. Although the clinical and population-wide impact of these tools continues to be elucidated, such transformative progress does not come without challenges, such as the concerns about adopting black box technologies, assessing input data quality for training such models, and the risk of perpetuating rather than alleviating health disparities. This review critically appraises the advances of machine learning related to the care of AF thus far, their potential future directions, and its potential limitations and challenges.

Abstract This is a protocol for a co‐registered Cochrane and Campbell Review (Methodology). The objectives are as follows: To identify, describe and assess methods for: when to replicate a systematic review; how to replicate a systematic review.

Atrial fibrillation (AF) is an important comorbidity in patients with end-stage renal disease (ESRD) undergoing dialysis that portends increased health care utilization, morbidity, and mortality in this already high-risk population. Patients with ESRD have a particularly high stroke risk, which is further compounded by AF. However, the role of anticoagulation for stroke prophylaxis in ESRD and AF is debated. The ESRD population presents a unique challenge because of the combination of elevated stroke and bleeding risks. Warfarin has been traditionally used in this population, but it is associated with significant risks of minor and major bleeding, particularly intracranial, thus leading many clinicians to forgo anticoagulation altogether. When anticoagulation is prescribed, rates of adherence and persistence are poor, leaving many patients untreated. The direct oral anticoagulants (DOACs) may offer an alternative to warfarin in ESRD patients, but these agents have not been extensively studied in this population and uncertainties regarding comparative effectiveness (versus warfarin, each other, and no treatment) remain. In this review, we discuss the current evidence on the risk and benefits of anticoagulants in this challenging population and comparisons between warfarin and DOACs, and review future directions including options for non-pharmacologic stroke prevention.

Background Atrial fibrillation is the most common arrhythmia worldwide. Data regarding 30‐day readmission rates after discharge for atrial fibrillation remain poorly reported. Methods and Results The Nationwide Readmission Database (2010–2014) was queried using the International Classification of Diseases, Ninth Revision ( ICD‐9 ) codes to identify study population. Incidence, etiologies of 30‐day readmission and predictors of 30‐day readmissions, and cost of care were analyzed. Among 1 723 378 patients who survived to discharge, 249 343 (14.4%) patients were readmitted within 30 days. Compared with the readmitted group, the nonreadmitted group had higher utilization of electrical cardioversion and catheter ablation. Atrial fibrillation was the most common cause of readmission (24.1%). Median time to 30‐day readmission was 13 days. Advancing age, female sex, and longer stay during index hospitalization predicted higher 30‐day readmissions, whereas private insurance, electrical cardioversion, catheter ablation, higher income, and elective admissions correlated with lower 30‐day readmission. Comorbidities such as heart failure, neurological disorder, chronic obstructive pulmonary disease, diabetes mellitus, chronic kidney disease, chronic liver failure, coagulopathy, anemia, peripheral vascular disease, and electrolyte disturbance, correlated with increased 30‐day readmissions and cost burden. Trend analysis showed a progressive decline in 30‐day readmission rates from 14.7% in 2010 to 14.3% in 2014 ( P trend, <0.001). Conclusions Approximately 1 in 7 patients were readmitted within 30 days of discharge, with symptomatic atrial fibrillation being the most common cause. We identified a predictive model for increased risk of readmissions and treatment expense. Electrical cardioversion during index admission was associated with a significant reduction in 30‐day readmissions and service charges. The 30‐day readmissions correlated with a substantial rise in the cost of care.

AbstractThere is increasing recognition of silent and clinically apparent thromboembolic events after left‐sided ventricular tachycardia (VT) ablation. However, unlike atrial fibrillation ablation procedures where postablation oral anticoagulation (OAC) is universal, there is significant practice variation in OAC use after VT ablation. Herein, we review the data on post‐VT ablation thromboembolism and evidence on the use of OAC, we suggest that OAC merits consideration in most cases after a balanced assessment of risks and benefits in individual patients, and we discuss future directions.