Background: Sleep-disordered breathing is highly prevalent in heart failure (HF) and has been suggested as a risk factor for malignant ventricular arrhythmias. The Respiratory Disturbance Index (RDI) computed by an implantable cardioverter-defibrillator (ICD) algorithm accurately identifies severe sleep apnea.
Objectives: In the present analysis, the authors evaluated the association between ICD-detected sleep apnea and the incidence of appropriate ICD therapies in patients with HF.
Introduction: The Respiratory Disturbance Index (RDI) computed by an implantable cardioverter defibrillator (ICD) algorithm accurately identifies severe sleep apnea (SA). In the present analysis, we tested the hypothesis that RDI could also predict atrial fibrillation (AF) burden.
Methods: Patients with ejection fraction ≤35% implanted with an ICD were enrolled and followed up for 24 months.
Aims: The utilization of remote monitoring platforms was recommended amidst the COVID-19 pandemic. The HeartLogic index combines multiple implantable cardioverter defibrillator (ICD) sensors and has proved to be a predictor of impending heart failure (HF) decompensation. We examined how multiple ICD sensors behave in the periods of anticipated restrictions pertaining to physical activity.
View Article and Find Full Text PDFBackground: The HeartLogic algorithm combines multiple implantable cardioverter-defibrillator sensors to identify patients at risk of heart failure (HF) events. We sought to evaluate the risk stratification ability of this algorithm in clinical practice. We also analyzed the alert management strategies adopted in the study group and their association with the occurrence of HF events.
View Article and Find Full Text PDFBackground: Sleep apnea, as measured by polysomnography, is associated with adverse outcomes in heart failure. The DASAP-HF (Diagnosis and Treatment of Sleep Apnea in Patient With Heart Failure) study previously demonstrated that the respiratory disturbance index (RDI) computed by the ApneaScan algorithm (Boston Scientific) accurately identifies severe sleep apnea in implantable cardioverter-defibrillator (ICD) patients.
Objective: The purpose of the long-term study phase was to assess the incidence of clinical events after 24 months and investigate the association with RDI values.
Purpose: Latency during left ventricle (LV) pacing has been suggested as a potential cause of ineffectual biventricular pacing. We assessed the incidence, predictors, and impact on outcome of increased LV latency in 274 patients undergoing cardiac resynchronization therapy (CRT).
Methods: On implantation, the latency interval was defined as the shortest stimulus-to-QRS onset interval in any lead of the 12-lead ECG.
Background: Sleep apnea (SA) is a relevant issue in the management of patients with heart failure for risk stratification and for implementing treatment strategies.
Objective: The purpose of this study was to evaluate in patients with implantable cardioverter-defibrillators (ICDs) the performance of the respiratory disturbance index (RDI) computed by the ApneaScan algorithm (Boston Scientific Inc., Natick, MA) as a discriminator of severe SA.
Aims: A recommendation for a subcutaneous-implantable cardioverter-defibrillator (S-ICD) has been added to recent European Society of Cardiology Guidelines. However, the S-ICD is not ideally suitable for patients who need pacing. The aim of this survey was to analyse the current practice of ICD implantation and to evaluate the actual suitability of S-ICD.
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