Myocardial Fibrosis as a Predictor of Sudden Death in Patients With Coronary Artery Disease

Zegard, Abbasin; Okafor, Osita; Bono, Joseph De; Kalla, Manish; Lencioni, Mauro; Marshall, Howard; Hudsmith, Lucy; Qiu, Tianyi; Steeds, Richard P.; Stegemann, Berthold; Leyva, Francisco

doi:10.1016/j.jacc.2020.10.046

Cited by 74 publications

(54 citation statements)

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“…In the CMR-SCD study, 7 clinical documentation and CMR reports were retrospectively screened to determine whether patients satisfied inclusion and exclusion criteria. Inclusion criteria were: CAD, defined as: (i) previous MI, percutaneous coronary intervention or coronary artery bypass grafting; or (ii) coronary angiography showing > _70% stenosis in > _1 coronary artery or > _50% stenosis of the left main stem; or (iii) MF on CMR in an ischaemic distribution; and (iv) LVEF >35% for the purposes of the present subanalysis.…”

Section: Methodsmentioning

confidence: 99%

“…4,5 In addition, the so-called greyzone fibrosis (GZF), an admixture of MF and viable tissue thought to be a substrate for ventricular arrhythmias, identifiable with CMR, has also been shown to be associated with ventricular arrhythmias in clinical studies. 6 The recent Cardiovascular Magnetic Resonance-Sudden Cardiac Death (CMR-SCD) study, which included patients with coronary artery disease (CAD) and a wide range of LVEFs, showed that GZF was as a strong predictor of SCD and a composite, arrhythmic endpoint of SCD, resuscitated cardiac arrest, VF or VT. 7 It also showed that 49% of SCDs occurred in patients with an LVEF >35%. The present subanalysis of the CMR-SCD study explores whether MF and GZF are associated with arrhythmic events in patients with CAD and an LVEF >35%.…”

Section: What's New?mentioning

confidence: 97%

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Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%

et al. 2021

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Aims To determine whether myocardial fibrosis and greyzone fibrosis (GZF) on cardiovascular magnetic resonance (CMR) is associated with ventricular arrhythmias in patients with coronary artery disease (CAD) and a left ventricular ejection fraction (LVEF) >35%. Methods and results In this retrospective study of CAD patients, GZF mass using the 3SD method (GZF3SD) and total fibrosis mass using the 2SD method (TF2SD) on CMR were assessed in relation to the primary, combined endpoint of sudden cardiac death, ventricular tachycardia, ventricular fibrillation, or resuscitated cardiac arrest. Among 701 patients [age: 65.8 ± 12.3 years (mean ± SD)], 28 (3.99%) patients met the primary endpoint over 5.91 years (median; interquartile range 4.42–7.64). In competing risks analysis, a GZF3SD mass ≥5.0 g was strongly associated with the primary endpoint [subdistribution hazard ratio (sHR): 17.4 (95% confidence interval, CI 6.64–45.5); area under receiver operator characteristic curve (AUC): 0.85, P < 0.001]. A weaker association was observed for TF2SD mass ≥23 g [sHR 10.4 (95% CI 4.22–25.8); AUC: 0.80, P < 0.001]. The range of sHRs for GZF3SD mass (1–527) was wider than for TF2SD mass (1–37.6). Conclusions In CAD patients with an LVEF >35%, GZF3SD mass was strongly associated with the arrhythmic endpoint. These findings hold promise for its use in identifying patients with CAD and an LVEF >35% at risk of arrhythmic events.

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Section: Methodsmentioning

confidence: 99%

Section: What's New?mentioning

confidence: 97%

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%

et al. 2021

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“…All datasets contain clinical information, medications and other selected variables such as ECG parameters and biomarkers, which were recorded for each patient at time of entry into the dataset. Some datasets include additional variables regarding cardiac magnetic resonance (CMR) imaging, which have been shown to be highly prognostic of SCD [24] (see Table 1 ). All data include information about outcomes during follow-up for each patient: until time of SCD, death from other causes, or until time of first appropriate ICD shocks/anti-tachycardia pacing, hereafter referred to as appropriate therapy.…”

Section: Methods and Analysismentioning

confidence: 99%

Development and Validation of a Multivariable Risk Prediction Model for Sudden Cardiac Death after Myocardial Infarction (PROFID Risk Model): Study Rationale, Design and Protocol

Martin

Hindricks

Akbarov

et al. 2021

Preprint

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Introduction Sudden cardiac death (SCD) is the leading cause of death in patients with myocardial infarction (MI) and can be prevented by the implantable cardioverter defibrillator (ICD). Currently, risk stratification for SCD and decision on ICD implantation are based solely on impaired left ventricular ejection fraction (LVEF). However, this strategy leads to over- and under-treatment of patients because LVEF alone is insufficient for accurate assessment of prognosis. Thus, there is a need for better risk stratification. This is the study protocol for developing and validating a prediction model for risk of SCD in patients with prior MI. Methods and Analysis The EU funded PROFID project will analyse 23 datasets from Europe, Israel and the US (~225,000 observations). The datasets include patients with prior MI or ischemic cardiomyopathy with reduced LVEF<50%, with and without a primary prevention ICD. Our primary outcome is SCD in patients without an ICD, or appropriate ICD therapy in patients carrying an ICD as a SCD surrogate. For analysis, we will stack 18 of the datasets into a single database (datastack), with the remaining analysed remotely for data governance reasons (remote data). We will apply 5 analytical approaches to develop the risk prediction model in the datastack and the remote datasets, all under a competing risk framework: 1) Weibull model, 2) flexible parametric survival model, 3) random forest, 4) likelihood boosting machine, and 5) neural network. These dataset-specific models will be combined into a single model (one per analysis method) using model aggregation methods, which will be externally validated using systematic leave-one-dataset-out cross-validation. Predictive performance will be pooled using random effects meta-analysis to select the model with best performance. Ethics and dissemination Local ethical approval was obtained. The final model will be disseminated through scientific publications and a web-calculator. Statistical code will be published through open-source repositories.

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“…Subsequent studies reinforced the role of LGE mass as an independent predictor of all-cause mortality [ 39 ]. Recently, the so called “grey zone fibrosis” mass defined on the basis of standard deviation from maximal signal intensity LGE was more strongly associated with SCD and VAs than LVEF [ 40 ].…”

Section: Risk Stratification Of Scd In Patients After Myocardial Infarction Without Severe Left Ventricular Dysfunctionmentioning

confidence: 99%

Sudden Cardiac Death in Patients with Heart Disease and Preserved Systolic Function: Current Options for Risk Stratification

Pannone

Falasconi

Cianfanelli

et al. 2021

JCM

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Sudden cardiac death (SCD) is the leading cause of cardiovascular mortality in patients with coronary artery disease without severe systolic dysfunction and in heart failure with preserved ejection fraction. From a global health perspective, while risk may be lower, the absolute number of SCDs in patients with left ventricle ejection fraction >35% is higher than in those with severely reduced left ventricle ejection fraction (defined as ≤35%). Despite these observations and the high amount of available data, to date there are no clear recommendations to reduce the sudden cardiac death burden in the population with mid-range or preserved left ventricle ejection fraction. Ongoing improvements in risk stratification based on electrophysiological and imaging techniques point towards a more precise identification of patients who would benefit from ICD implantation, which is still an unmet need in this subset of patients. The aim of this review is to provide a state-of-the-art approach in sudden cardiac death risk stratification of patients with mid-range and preserved left ventricular ejection fraction and one of the following etiologies: ischemic cardiomyopathy, heart failure, atrial fibrillation or myocarditis.

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Myocardial Fibrosis as a Predictor of Sudden Death in Patients With Coronary Artery Disease

Cited by 74 publications

References 32 publications

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%

Development and Validation of a Multivariable Risk Prediction Model for Sudden Cardiac Death after Myocardial Infarction (PROFID Risk Model): Study Rationale, Design and Protocol

Sudden Cardiac Death in Patients with Heart Disease and Preserved Systolic Function: Current Options for Risk Stratification

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Myocardial Fibrosis as a Predictor of Sudden Death in Patients With Coronary Artery Disease

Cited by 74 publications

References 32 publications

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction &gt;35%

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction &gt;35%

Development and Validation of a Multivariable Risk Prediction Model for Sudden Cardiac Death after Myocardial Infarction (PROFID Risk Model): Study Rationale, Design and Protocol

Sudden Cardiac Death in Patients with Heart Disease and Preserved Systolic Function: Current Options for Risk Stratification

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Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%

Greyzone myocardial fibrosis and ventricular arrhythmias in patients with a left ventricular ejection fraction >35%