Search Results (3)

Implantable Cardioverter-Defibrillators (ICDs) are life-sustaining devices used in the prevention of sudden death in patients suffering from advanced cardiac diseases. Although improvements in ICD technology and monitoring capabilities have been made, existing techniques are still not effective in predicting accelerated battery drain, thereby causing unplanned generator replacement and clinically significant device-related events. In this study, machine learning techniques were employed in the assessment of the early detection of ICD battery depletion risk using the collected device interrogation reports. The dataset used consisted of 32 devices in the training set and nine in the testing set. In order to mitigate the problem of a small sample size, a GMM-based data augmentation technique was applied solely to the training data, and actual devices were used for the testing data. Five supervised models, including Logistic Regression, Random Forest, SVM, CatBoost, and a Neural Network (MLP), have been utilized using a repeated stratified cross-validation and a separate held-out test data set. All the models have been tested for their performance using classification metrics. All models demonstrated variable performance with wide confidence intervals due to limited sample size. Support vector machines showed the highest cross-validation discrimination 0.889 ± 0.203, though uncertainty remains substantial given the small datasets (n = 41). From the feature analysis, it was found that atrial sensing amplitude, RV/LV capture threshold, output settings, and implant duration were the most important features for the prediction of high battery depletion risk. These findings suggest that changes in device parameters and implant age are associated with elevated battery depletion risk, supporting the feasibility of telemetry-driven risk stratification for device management. Full article

Background/Objectives: Ventricular fibrillation (VF) is the most common shockable rhythm in cardiac arrest, yet refractory VF (RVF), defined as persistent VF after ≥three failed defibrillation attempts, poses a significant challenge. Two alternative strategies, double sequential external defibrillation (DSED) and vector change (VC) defibrillation, aim to enhance defibrillation success where conventional methods fail. This review evaluates the clinical feasibility, safety, and implementation barriers of DSED and VC in RVF cases. Methods: A systematic review was conducted following PRISMA 2020 guidelines. PubMed, Scopus, and CINAHL databases were searched for studies published between January 2015 and August 2025. Eligible studies included adult RVF patients treated with DSED or VC. Outcomes assessed included implementation barriers, safety concerns, and methodological limitations. Study quality was evaluated using the Newcastle–Ottawa Scale and the Cochrane RoB 2 tool. Results: Sixteen studies met the inclusion criteria. Identified barriers were grouped into practical and methodological categories. Practical barriers included the need for dual defibrillators and pads, delays in shock coordination, inconsistent protocols, equipment compatibility issues, and dependence on trained personnel. Methodological barriers included small sample sizes, retrospective designs, inconsistent RVF definitions, and incomplete reporting of neurological outcomes. Conclusions: DSED and VC defibrillation may offer potential benefits in managing RVF, but their use is hindered by significant practical and methodological barriers. Due to the limited number of randomized trials, further high-quality studies with standardized definitions and safety endpoints are needed to clarify their clinical utility and inform implementation. Full article

Background: Refractory ventricular fibrillation (RVF) is a life-threatening condition characterized by the persistence of ventricular fibrillation despite multiple defibrillation attempts. It represents a critical challenge in out-of-hospital cardiac arrest management, with poor survival outcomes and limited guidance from current resuscitation guidelines. In recent years, alternative defibrillation strategies (ADSs), including dual sequential external defibrillation (DSED) and vector change defibrillation (VCD), have emerged as potential interventions to improve defibrillation success and patient outcomes. However, their clinical utility remains debated due to heterogeneous evidence and limited high-quality data. Methods: This narrative review explores the current landscape of ADSs in patients with RVF. MEDLINE, Google Scholar, the World Health Organization, LitCovid NLM, EMBASE, CINAHL Plus, and the Cochrane Library were examined from their inception to April 2025. Results: The available literature is dominated by retrospective studies and case series, with only one randomized controlled trial (DOSE-VF). This trial demonstrated improved survival to hospital discharge with ADSs compared to standard defibrillation. DSED was associated with higher rates of return of spontaneous circulation and favorable neurological outcomes. However, subsequent meta-analyses have produced inconsistent results, largely due to the heterogeneity of the included studies. The absence of sex-, gender-, and ethnicity-specific analyses further limits the generalizability of the findings. In addition, practical barriers, such as equipment availability, pose significant challenges to implementation. Conclusions: ADSs represent a promising yet still-evolving approach to the management of RVF, with DSED showing the most consistent signal of benefit. Further high-quality research is required to enhance generalizability and generate more definitive, high-level evidence. Full article