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The current guidelines advocate prophylactic implantable cardioverter-defibrillator (ICD) for all patients with symptomatic heart failure (HF) with low left ventricular ejection fraction. Because many patients will never use their device, a score delineating subgroups with differential ICD benefit is crucial. We aimed to evaluate the MADIT-II-based Risk Stratification Score (MRSS) feasibility to delineate the ICD survival benefit in a nationwide registry of patients with HF with prophylactic ICDs. Accordingly, all Israeli patients with HF with prophylactic ICD/cardiac resynchronization therapy defibrillators were categorized into MRSS-based risk subgroups. The study end points included overall mortality, sustained ventricular arrhythmia (VA), and a competing risk of VA (potential preventable arrhythmic death, where ICD could benefit survival) versus nonarrhythmic death. Potential ICD survival benefit was estimated by the area between these cumulative incidence curves. In 2,177 patients with HF implanted prophylactic device, 189 patients (8.7%) had VA and 316 (14.5%) died during a median follow-up of 2.9 years. The MRSS risk subgroups were significantly associated with overall mortality (p <0.001) and weakly with VA (p = 0.3). The competing risk analysis of VA versus nonarrhythmic death revealed a significantly shorter duration (p <0.001) and smaller magnitude of ICD survival benefit with increased risk subgroups, yielding an estimated 76, 60, 38, and 0 life days gained from prophylactic ICD implant during a 5-year follow-up for the MRSS low-, intermediate-, high-, and very high-risk subgroups, respectively (p for trend <0.05). In conclusion, MRSS use in a nationwide registry of patients with ischemic and nonischemic cardiomyopathy, revealed subgroups with differing ICD survival benefit, suggesting it could help evaluate prophylactic ICD survival benefit., Competing Interests: Declaration of Competing Interest The authors have no competing interest to declare., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Aims: Intraoperative defibrillation testing (DT) during implant or replacement of implantable cardioverter-defibrillators (ICDs) has been a matter of debate for many years. This debate was put to rest by the Simple and Nordic ICD trials, and the practice of testing during new implantations has essentially been almost abandoned. Old registries demonstrated an increased incidence of significant findings in DT during replacements. The aim of the present study was to evaluate frequency of significant findings and safety of DT in subjects undergoing device replacement., Methods and Results: A prospective observational multi-centre study included consecutive patients undergoing ICD generator replacement. The primary outcome was a failure to terminate induced ventricular fibrillation (VF) with a single shock 10 J below the maximal capacity of the device. Secondary outcomes included complications of DT. Patients were followed-up at 1- and 6-months post-procedure. A total of 92 patients were eligible, and consented to the study, of which 84 underwent DT during battery replacement. The median age was 68 years and 79.8% were males. Induction of VF was successful in 84 patients as was a successful conversion on the first attempt in all. There were no procedure-related complications. During follow up one patient had two appropriate ICD shock events. In four patients, ICD programming was changed. None suffered inappropriate shock. There was no evidence of lead malfunction. Two deaths occurred, none of which was related to arrhythmia., Conclusion: The present study found DT was not associated with complications in patients undergoing ICD generator replacement but produced no clinically important information., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: The aims of this study is to characterize the transvenous lead extraction (TLE) population with active (A) compared with passive fixation (PFix) leads and to compare the safety, efficacy, and ease of extracting active fixation (AFix) compared with PFix right atrial (RA) and right ventricular (RV) leads., Methods and Results: The European Lead Extraction ConTRolled Registry (ELECTRa) was analysed. Patients were divided into three groups; those with only AFix, only PFix, and combined Fix leads. Three outcomes were defined. Difficult extraction, complete radiological, and clinical success. Multivariate model was used to analyse the independent effect of Fix mechanism on these outcomes. The study included 2815 patients, 1456 (51.7%) with only AFix leads, 982 (34.9%) with only PFix leads, and 377 (13.4%) with combined Fix leads. Patients with AFix leads were younger with shorter lead dwelling time. Infection was the leading cause for TLE among the combined Fix group with lowest rates among AFix group. No difference in complications rates was noted between patients with only AFix vs. PFix leads. Overall, there were 1689 RA (1046 AFix and 643 PFix) and 2617 RV leads (1441 AFix and 1176 PFix). Multivariate model demonstrated that PFix is independently associated with more difficult extraction for both RA and RV leads, lower radiological success in the RA but has no effect on clinical success., Conclusion: Mechanism of Fix impact the ease of TLE of RA and RV leads and rates of complete radiological success in the RA but not clinical success. These findings should be considered during implantation and TLE procedures., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.)

Patients with life-threatening arrhythmias are often treated with cardiac implantable electronic devices (CIEDs), such as pacemakers and implantable cardioverter defibrillators (ICDs). Recent advancements in CIEDs have enabled advanced functionality and connectivity that make such devices (particularly ICDs) vulnerable to cyber-attacks. One of the most dangerous attacks on CIED ecosystems is a data manipulation attack from a compromised programmer device that sends malicious clinical programmings to the CIED. Such attacks can affect the CIED functioning and impact patient's survival and quality of life. In this paper, we propose Cardio-ML - an automated system for the detection of malicious clinical programmings that is based on machine learning algorithms and a novel missing values resemblance framework. Our system is designed to detect new variants of existing attacks and, more importantly, new unknown (zero-day) attacks, aimed at ICDs. We collected 1651 legitimate clinical programmings from 514 patients, over a four-year period, from programmer devices at two medical centers. Our collection also includes 28 core malicious functionalities created by cardiac electrophysiology experts that were later used to create different variants of malicious programmings. Cardio-ML was evaluated extensively in three comprehensive experiments and showed high detection capabilities in most attack scenarios. We achieved perfect classification results for detecting newly created variants of existing core malicious functionalities, with an AUC of 100%; for completely new unknown (zero-day) malicious clinical programmings, an AUC of 80% was obtained, which is 14% better than the state-of-the-art method. We were able to further improve our detection results by identifying the best combination of legitimate and zero-day malicious programmings in the dataset, achieving an AUC of 87%. CIED clinical programmings have many parameters without values for a large number of samples (programmings). To cope with the extreme amount of missing values in our dataset, we developed a novel missing values-based resemblance framework and evaluated it using three dataset-creation approaches: a standard expert-driven approach, our novel data-driven approach, and a combined approach incorporating both approaches. The results showed that our novel framework handles missing values in the data better than the expert-driven approach which yields an empty dataset. In particular, the combined approach showed a 40% improvement in data utilization compared to the data-driven approach., (Copyright © 2021 Elsevier B.V. All rights reserved.)