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Background Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD). Objectives The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD). Methods Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD. Results Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell’s C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell’s C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models. Conclusions Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

Acute myocarditis is an inflammatory condition that may herald the onset of dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM). We investigated the frequency and clinical consequences of DCM and ACM genetic variants in a population-based cohort of patients with acute myocarditis. This was a population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA sequencing for well-characterized cardiomyopathy-associated genes with comparison to healthy controls (n=1053) sequenced on the same platform. Case ascertainment in England was assessed against national hospital admission data. The primary outcome was all-cause mortality. Variants that would be considered pathogenic if found in a patient with DCM or ACM were identified in 8% of myocarditis cases compared with

BackgroundGuidelines recommend genetic testing and cardiovascular magnetic resonance (CMR) for the investigation of dilated cardiomyopathy (DCM). However, the incremental value is unclear. We assessed the impact of these investigations in determining etiology.MethodsSixty consecutive patients referred with DCM and recruited to our hospital biobank were selected. Six independent experts determined the etiology of each phenotype in a step-wise manner based on (1) routine clinical data, (2) clinical and genetic data and (3) clinical, genetic and CMR data. They indicated their confidence (1-3) in the classification and any changes to management at each step.ResultsSix physicians adjudicated 60 cases. The addition of genetics and CMR resulted in 57 (15.8%) and 26 (7.2%) changes in the classification of etiology, including an increased number of genetic diagnoses and a reduction in idiopathic diagnoses. Diagnostic confidence improved at each step (p < 0.0005). The number of diagnoses made with low confidence reduced from 105 (29.2%) with routine clinical data to 71 (19.7%) following the addition of genetics and 37 (10.3%) with the addition of CMR. The addition of genetics and CMR led to 101 (28.1%) and 112 (31.1%) proposed changes to management, respectively. Interobserver variability showed moderate agreement with clinical data (κ = 0.44) which improved following the addition of genetics (κ = 0.65) and CMR (κ = 0.68).ConclusionWe demonstrate that genetics and CMR, frequently changed the classification of etiology in DCM, improved confidence and interobserver variability in determining the diagnosis and had an impact on proposed management.

Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Unrestricted educational grants Background Increasing evidence supports a link between myocardial fibrosis (MF) and ventricular arrhythmias. We sought to determine whether presence of MF on visual assessment (MFVA) and gray zone fibrosis (GZF) mass predicts SCD and ventricular fibrillation / sustained ventricular tachycardia after cardiac implantable electronic device (CIED) implantation. Methods In this prospective study, total fibrosis and GZF mass, quantified using cardiovascular magnetic resonance, was assessed in relation to the primary endpoint of sudden cardiac death (SCD) and the secondary, arrhythmic endpoint of SCD or ventricular arrhythmias after CIED implantation. Results Among 700 patients (age 68.0 ± 12.0yrs [mean ± SD]), 27 (3.85%) experienced a SCD and 121 (17.3%) met the arrhythmic endpoint over 6.93 yrs (median; interquartile range 5.82-9.32). MFVA predicted SCD (hazard ratio [HR]: HR:26.3 [95% confidence interval [CI] 3.70-3337]; negative predictive value: 100%). In competing risks analyses, MFVA also predicted the arrhythmic endpoint (subdistribution [sHR]: 19.9 [95% CI 6.40-61.9]; negative predictive value:98.6%). Compared with no MFVA, a GZF mass measured with the 5SD method (GZF5SD) > 17 g was associated with highest risk of SCD (HR: 44.6;95% CI 6.12-5685) and the arrhythmic endpoint (sHR: 30.3 [95% CI 9.60-95.8]). Adding GZF5SD mass to MFVA led to reclassification of 39% for SCD and 50.2% for the arrhythmic endpoint. In contrast, LVEF did not predict either endpoint. Conclusions In CIED recipients, MFVA excluded patients at risk of SCD and virtually excluded ventricular arrhythmias. Quantified GZF5SD mass added predictive value in relation to SCD and the arrhythmic endpoint.

Objectives(1) To evaluate the prevalence and hospitalisation rate of COVID-19 infections among patients with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) in the Royal Brompton and Harefield Hospital Cardiovascular Research Centre (RBHH CRC) Biobank. (2) To evaluate the indirect impact of the pandemic on patients with cardiomyopathy through the Heart Hive COVID-19 study. (3) To assess the impact of the pandemic on national cardiomyopathy-related hospital admissions.Methods(1) 1236 patients (703 DCM, 533 HCM) in the RBHH CRC Biobank were assessed for COVID-19 infections and hospitalisations; (2) 207 subjects (131 cardiomyopathy, 76 without heart disease) in the Heart Hive COVID-19 study completed online surveys evaluating physical health, psychological well-being, and behavioural adaptations during the pandemic and (3) 11 447 cardiomyopathy-related hospital admissions across National Health Service (NHS) England were studied from NHS Digital Hospital Episode Statistics over 2019–2020.ResultsA comparable proportion of patients with cardiomyopathy in the RBHH CRC Biobank had tested positive for COVID-19 compared with the UK population (1.1% vs 1.6%, p=0.14), but a higher proportion of those infected were hospitalised (53.8% vs 16.5%, p=0.002). In the Heart Hive COVID-19 study, more patients with cardiomyopathy felt their physical health had deteriorated due to the pandemic than subjects without heart disease (32.3% vs 13.2%, p=0.004) despite only 4.6% of the cardiomyopathy cohort reporting COVID-19 symptoms. A 17.9% year-on-year reduction in national cardiomyopathy-related hospital admissions was observed in 2020.ConclusionPatients with cardiomyopathy had similar reported rates of testing positive for COVID-19 to the background population, but those with test-proven infection were hospitalised more frequently. Deterioration in physical health amongst patients could not be explained by COVID-19 symptoms, inferring a significant contribution of the indirect consequences of the pandemic.Trial registration numberNCT04468256

During pregnancy the maternal heart undergoes significant physiological change. Technological advancements in echocardiography (echo) have improved our ability to assess the right heart in detail and yet there is little research into adaptation during pregnancy. In this pilot study, we considered how three measures of right heart function changed in normal women from the 1st trimester through to the post-partum period. We observed a significant increase in tricuspid annulus planar systolic excursion (TAPSE) and right ventricular systolic velocity (RV S’) from the 1st to the 2nd trimester; both measures of longitudinal right ventricular function. There was no significant difference in right ventricular systolic area change, which is more difficult to accurately measure, and reflects radial function. TAPSE and RV S’ are easy to accurately measure with modern echo technology. This pilot study suggests that any reduction in these values from the 1st to the 2nd trimester should prompt more detailed assessment, and correlation with clinical symptoms. It would be valuable to undertake a comprehensive study to define normal ranges for common measures of right ventricular function, using echo, during pregnancy. The ability to assess the right heart, with an understanding of expected normal values, has the potential to significantly improve our understanding and management of maternal cardiovascular disease.

Background: Acute myocarditis is a complex inflammatory disease increasingly associated with dilated cardiomyopathy (DCM) and arrhythmogenic ventricular cardiomyopathy (ACM), but its underlying genetic basis is unknown. We sought to determine if there is a genetic overlap between myocarditis and inherited forms of cardiomyopathy. Methods: Population-based cohort of 336 consecutive patients with acute myocarditis enrolled in London and Maastricht. All participants underwent targeted DNA-sequencing for well-characterised cardiomyopathy-associated genes with comparison to healthy controls (n=1053). Case ascertainment was assessed against national admission data. Findings: Variants of known or likely pathogenicity were identified in 6% of cases compared to