Importance
Current guidelines do not recommend primary prevention implantable cardioverter-defibrillators (ICDs) unless a patient's left ventricular ejection fraction (LVEF) is 35% or less. Many sudden cardiac deaths (SCD) occur when LVEF is 36% to 50%. Myocardial scar (a key arrhythmic substrate) can be assessed by late gadolinium enhancement on cardiovascular magnetic resonance (CMR), but robust evidence is lacking regarding a scar-based approach to ICD insertion.
Objective
To determine whether implantation of ICDs reduces SCD or hemodynamically significant ventricular arrhythmia (HSVA) in patients with an LVEF of 36% to 50% and myocardial scar.
Design, Setting, and Participants
An open-label randomized clinical trial enrolled adults between 2015 and 2022 who had ischemic or nonischemic cardiomyopathy, an LVEF of 36% to 50%, CMR-defined myocardial scar, and were receiving guideline-directed medical therapy at 18 sites in Australia, Germany, and the UK. Follow-up assessments were completed in 2026.
Interventions
A primary prevention ICD (n = 180) vs an implantable loop recorder (ILR) (n = 173).
Main Outcomes and Measures
The primary composite outcome was SCD or HSVA. Five secondary outcomes were evaluated: SCD, HSVA, heart failure-related hospitalization, cardiovascular mortality, and all-cause mortality.
Results
Of 353 patients randomized (median age, 65 years [IQR, 57-61 years]; 18% female; and 72% had an ischemic etiology), 70% had an LVEF of 40% or greater. The median follow-up was 6.3 years (IQR, 4.8-7.6 years). The primary composite outcome occurred in 14 patients (7.8%) in the ICD group compared with 16 patients (9.2%) in the ILR group (hazard ratio [HR], 0.76 [95% CI, 0.37-1.58]). For the individual components of the primary composite outcome, SCD occurred in 3 patients (1.7%) vs 10 patients (5.8%) in the ILR group (HR, 0.26 [95% CI, 0.07-0.95]) and HSVA occurred in 12 patients (6.7%) vs 6 patients (3.5%), respectively (HR, 1.77 [95% CI, 0.65-4.81]). The rates for all-cause mortality, cardiovascular mortality, and heart failure-related hospitalization were similar between groups. In a prespecified analysis of 6 subgroups, the primary outcome occurred less often in patients younger than 70 years in the ICD group (3.3%) vs patients in the ILR group (10.0%) (HR, 0.28 [95% CI, 0.09-0.89]) but not in those aged 70 years or older (16.9% vs 7.5%, respectively) (HR, 2.33 [95% CI, 0.75-7.26]; P = .01 for interaction).
Conclusions and Relevance
Implantation of an ICD did not reduce the composite outcome of SCD or HSVA in patients with an LVEF of 36% to 50% and myocardial scar.
Trial Registration
ClinicalTrials.gov Identifier: NCT01918215.
J. Selvanayagam, John G. F. Cleland, G. Hillis et al.· Journal of the American Medi...· 0 citations
Atrial fibrillation (AF) is the most prevalent sustained arrhythmia worldwide. Acute myocardial infarction (AMI) is closely intertwined with AF through a bidirectional relationship: pre-existing AF is associated with increased risk of AMI, while AMI predisposes to new-onset atrial fibrillation (NOAF). This narrative review synthesizes evidence on the global burden of AF in the setting of AMI: pre-existing AF, NOAF following AMI, and the prognostic implications of AF in AMI, encompassing the 'past, present and future' of AF in AMI. Pre-existing AF is present in 3%-4% of patients with AMI and has demonstrated an independent association with acute coronary syndromes, mediated by systemic inflammation, prothrombotic states, demand ischemia, and coronary thromboembolism. NOAF complicates 5%-20% of AMI cases, with peak onset within the first six months. Predictive factors include age, comorbidities such as chronic kidney disease, markers of inflammation (including systemic immune-inflammation index and hs-CRP), neurohormonal activation (NT-proBNP), echocardiographic parameters of diastolic dysfunction and left atrial strain, and electrocardiographic features such as QRS fragmentation. Multiple predictive models for NOAF have been developed with varying discriminatory performance. Emerging research suggests that machine learning may provide superior risk stratification, though further study is needed. AF in the context of AMI confers substantially increased risk of mortality, stroke, bleeding, and heart failure, with NOAF showing particularly strong prognostic significance. Improved recognition of predictive markers, alongside development of tailored prognostic models, is essential to guide antithrombotic therapy and optimize outcomes in this high-risk population.
E. Xiong, S. Prasad, John J. Atherton et al.· Pacing and clinical electrop...· 0 citations
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