Who Benefits From a Defibrillator—Balancing the Risk of Sudden Versus Non-sudden Death

Abstract

Purpose of ReviewTreatment with a defibrillator can reduce the risk of sudden death by terminating ventricular arrhythmias. The identification of patient groups in whom this function reduces overall mortality is challenging. In this review, we summarise the evidence for who benefits from a defibrillator.Recent FindingsRecent evidence suggests that contemporary pharmacologic and non-defibrillator device therapies are altering the potential risks and benefits of a defibrillator.SummaryWho benefits from a defibrillator is determined by both the risk of sudden death and the competing risk of other, non-sudden causes of death. The balance of these risks is changing, which calls into question whether historic evidence for the use of defibrillators remains robust in the modern era.

Usefulness of the MAGGIC Score in Predicting the Competing Risk of Non-Sudden Death in Heart Failure Patients Receiving an Implantable Cardioverter-Defibrillator: A Sub-Analysis of the OBSERVO-ICD Registry

“…There has been considerable debate on this issue, particularly in the primary prevention setting [ 9 ], but few works to date have addressed it convincingly with appropriate competing risk analysis, which follows separate survival models estimating cause-specific hazard ratios for non-sudden death vs. ICD therapy [ 10 , 11 , 14 , 15 ]. In 2008, Koller and colleagues published a first landmark analysis of 442 ICD recipients who nonetheless were mostly implanted for secondary prevention (59% vs. 9% in our sample) and seldom received a biventricular pacemaker (16% vs. 44% in our sample) [ 10 ].…”

“…A growing number of reports emphasize the clinical relevance of the competing risk of non-sudden death in this population, particularly in the presence of comorbidities [ 8 ]. Overall, only about a quarter of these ICD recipients experience the ideal clinical course of receiving a protection from life-limiting ventricular arrhythmias and surviving for a reasonable period of time [ 9 , 10 , 11 ].…”

Incorporating machine learning into the decision-making process regarding implantable cardioverter-defibrillator treatment

“…In predicting the benefit from defibrillator treatment, data such as patients’ The New York Heart Association (NYHA) functional classes, left ventricular ejection fraction (LVEF) values, the presence of ventricular aneurysm or scar tissue detected by imaging methods, history of syncope, and atrial fibrillation (AF) have been shown to be useful. 2 , 3 Providência et al 4 revealed that using NYHA, LVEF, and AF in risk scoring can be useful in identifying those who will benefit from defibrillator therapy. Adding these data, which have been shown to be useful in past studies, to multimodal machine learning could contribute to the study.…”

Left ventricular pacing induced polymorphic ventricular tachycardia via the adaptive left ventricle pacing algorithm

“…Implantable cardioverter defibrillator (ICD) therapy is associated with a reduction in sudden arrhythmic death 1 . Cardiac resynchronization therapy (CRT) with (CRT‐D) or without (CRT‐P) defibrillator is also associated with improvements in survival, heart failure symptoms, and quality of life in those with left bundle branch block and prolonged QRS duration 2 .…”