Dataset Information

Late-Gadolinium Enhancement Interface Area and Electrophysiological Simulations Predict Arrhythmic Events in Patients With Nonischemic Dilated Cardiomyopathy.

ABSTRACT:

Objectives

This study sought to investigate whether shape-based late gadolinium enhancement (LGE) metrics and simulations of re-entrant electrical activity are associated with arrhythmic events in patients with nonischemic dilated cardiomyopathy (NIDCM).

Background

The presence of LGE predicts life-threatening ventricular arrhythmias in NIDCM; however, risk stratification remains imprecise. LGE shape and simulations of electrical activity may be able to provide additional prognostic information.

Methods

Cardiac magnetic resonance (CMR)-LGE shape metrics were computed for a cohort of 156 patients with NIDCM and visible LGE and tested retrospectively for an association with an arrhythmic composite endpoint of sudden cardiac death and ventricular tachycardia. Computational models were created from images and used in conjunction with simulated stimulation protocols to assess the potential for re-entry induction in each patient's scar morphology. A mechanistic analysis of the simulations was carried out to explain the associations.

Results

During a median follow-up of 1,611 (interquartile range: 881 to 2,341) days, 16 patients (10.3%) met the primary endpoint. In an inverse probability weighted Cox regression, the LGE-myocardial interface area (hazard ratio [HR]: 1.75; 95% confidence interval [CI]: 1.24 to 2.47; p = 0.001), number of simulated re-entries (HR: 1.40; 95% CI: 1.23 to 1.59; p < 0.01) and LGE volume (HR: 1.44; 95% CI: 1.07 to 1.94; p = 0.02) were associated with arrhythmic events. Computational modeling revealed repolarization heterogeneity and rate-dependent block of electrical wavefronts at the LGE-myocardial interface as putative arrhythmogenic mechanisms directly related to the LGE interface area.

Conclusions

The area of interface between scar and surviving myocardium, as well as simulated re-entrant activity, are associated with an elevated risk of major arrhythmic events in patients with NIDCM and LGE and represent novel risk predictors.

SUBMITTER: Balaban G

PROVIDER: S-EPMC7900608 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Late-Gadolinium Enhancement Interface Area and Electrophysiological Simulations Predict Arrhythmic Events in Patients With Nonischemic Dilated Cardiomyopathy.

Balaban Gabriel G Halliday Brian P BP Porter Bradley B Bai Wenjia W Nygåard Ståle S Owen Ruth R Hatipoglu Suzan S Ferreira Nuno Dias ND Izgi Cemil C Tayal Upasana U Corden Ben B Ware James J Pennell Dudley J DJ Rueckert Daniel D Plank Gernot G Rinaldi Christopher A CA Prasad Sanjay K SK Bishop Martin J MJ

JACC. Clinical electrophysiology 20201029 2

<h4>Objectives</h4>This study sought to investigate whether shape-based late gadolinium enhancement (LGE) metrics and simulations of re-entrant electrical activity are associated with arrhythmic events in patients with nonischemic dilated cardiomyopathy (NIDCM).<h4>Background</h4>The presence of LGE predicts life-threatening ventricular arrhythmias in NIDCM; however, risk stratification remains imprecise. LGE shape and simulations of electrical activity may be able to provide additional prognost ...[more]

PMID: 33602406

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Project description:BackgroundPractice guidelines suggest the use of implantable cardioverter-defibrillators in patients with left ventricular ejection fractions (LVEF) ≤ 35% despite 3 to 6 months of guideline-directed medical therapy (GDMT). It remains unclear whether this strategy is appropriate for patients with dilated cardiomyopathy (DCM), who can experience reverse ventricular remodeling for up to 24 months after the initiation of GDMT. The aim of this study was to assess the longitudinal dynamic relationship between LVEF ≤ 35% and arrhythmic risk in patients with recent-onset nonischemic DCM on GDMT.MethodsA retrospective analysis was conducted among patients with recent-onset DCM (≤6 months) and recent initiation of GDMT (≤3 months) consecutively enrolled in a longitudinal registry. Risk for major ventricular arrhythmic events or sudden cardiac death was assessed in relationship to LVEF ≤ 35% at enrollment and 6 and 24 months after initiation of GDMT.ResultsFive hundred forty-four patients met the inclusion criteria. LVEF ≤ 35% identified patients with increased risk for major ventricular arrhythmic events or sudden cardiac death starting from 24 months after initiation of GDMT (hazard ratio, 2.126; 95% CI, 1.065-4.245; P = .03). However, LVEF ≤ 35% at presentation or 6 months after enrollment did not have prognostic significance. Sixty-seven percent of 131 patients with LVEF ≤ 35% at 6 months after initiation of GDMT had improved LVEFs (to >35%) by 24 months. This late LVEF improvement correlated with lower arrhythmic risk (P = .012) and was preceded by a reduction of LV dimensions in the first 6 months of GDMT.ConclusionsIn patients with DCM, the present findings suggest that risk stratification for major ventricular arrhythmic events or sudden cardiac death on the basis of LVEF ≤ 35% is effective after 2 years of GDMT, but not after 6 months. In selected patients with DCM, it would be appropriate to wait 24 months before primary prevention ICD implantation.

Project description:OBJECTIVES:The aim of this study was to evaluate the prognostic value of cardiac magnetic resonance (CMR) feature-tracking-derived global longitudinal strain (GLS) in a large multicenter population of patients with ischemic and nonischemic dilated cardiomyopathy. BACKGROUND:Direct assessment of myocardial fiber deformation with GLS using echocardiography or CMR feature tracking has shown promise in providing prognostic information incremental to ejection fraction (EF) in single-center studies. Given the growing use of CMR for assessing persons with left ventricular (LV) dysfunction, we hypothesized that feature-tracking-derived GLS may provide independent prognostic information in a multicenter population of patients with ischemic and nonischemic dilated cardiomyopathy. METHODS:Consecutive patients at 4 U.S. medical centers undergoing CMR with EF <50% and ischemic or nonischemic dilated cardiomyopathy were included in this study. Feature-tracking GLS was calculated from 3 long-axis cine-views. The primary endpoint was all-cause death. Cox proportional hazards regression modeling was used to examine the association between GLS and death. Incremental prognostic value of GLS was assessed in nested models. RESULTS:Of the 1,012 patients in this study, 133 died during median follow-up of 4.4 years. By Kaplan-Meier analysis, the risk of death increased significantly with worsening GLS tertiles (log-rank p < 0.0001). Each 1% worsening in GLS was associated with an 89.1% increased risk of death after adjustment for clinical and imaging risk factors including EF and late gadolinium enhancement (LGE) (hazard ratio [HR]:1.891 per %; p < 0.001). Addition of GLS in this model resulted in significant improvement in the C-statistic (0.628 to 0.867; p < 0.0001). Continuous net reclassification improvement (NRI) was 1.148 (95% confidence interval: 0.996 to 1.318). GLS was independently associated with death after adjustment for clinical and imaging risk factors (including EF and late gadolinium enhancement) in both ischemic (HR: 1.942 per %; p < 0.001) and nonischemic dilated cardiomyopathy subgroups (HR: 2.101 per %; p < 0.001). CONCLUSIONS:CMR feature-tracking-derived GLS is a powerful independent predictor of mortality in a multicenter population of patients with ischemic or nonischemic dilated cardiomyopathy, incremental to common clinical and CMR risk factors including EF and LGE.

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Dataset Information

Late-Gadolinium Enhancement Interface Area and Electrophysiological Simulations Predict Arrhythmic Events in Patients With Nonischemic Dilated Cardiomyopathy.

Objectives

Background

Methods

Results

Conclusions

Publications

Late-Gadolinium Enhancement Interface Area and Electrophysiological Simulations Predict Arrhythmic Events in Patients With Nonischemic Dilated Cardiomyopathy.

Similar Datasets

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