Petersen, Steffen E.

Abstract The management of acute myocarditis (AM) is addressed in multiple clinical guidelines. We systematically reviewed current guidelines developed by national and international medical organizations on the management of AM to aid clinical practice. Publications in MEDLINE, EMBASE and Cochrane were identified between 1 January 2013 and 12 April 2024. Additionally, the websites of relevant organizations and the Guidelines International Network, Guideline Central, and NHS knowledge and library hub were reviewed. Two reviewers independently screened titles and abstracts, two reviewers assessed the rigour of guideline development, and one reviewer extracted the recommendations. Two of the three guidelines identified showed good rigour of development. Those rigorously developed agreed on the definition of AM, sampling serum troponin as part of the workflow for AM, testing for B-type natriuretic peptides in heart failure, key diagnostic imaging in the form of cardiovascular magnetic resonance, coronary angiography to exclude significant coronary disease, indications for endomyocardial biopsy (EMB), and indications for immunosuppression and advanced treatment options. Discrepancies exist in sampling creatine kinase-myocardial bound as a marker of myocardial injury, indications for EMB, and indications for immunosuppression and treatment of uncomplicated AM. Evidence is lacking for the use of 18F-Fluorodeoxyglucose Positron Emission Tomography for myocardial imaging, exercise restriction, follow-up measures, and genetic testing, and there are few high-quality randomized trials to support treatment recommendations. Recommendations for management of AM in the guidelines have largely been developed from expert opinion rather than trial data.

Abstract Cardiac sarcoidosis (CS) is a form of inflammatory cardiomyopathy associated with significant clinical complications such as high-degree atrioventricular block, ventricular tachycardia, and heart failure as well as sudden cardiac death. It is therefore important to provide an expert consensus statement summarizing the role of different available diagnostic tools and emphasizing the importance of a multidisciplinary approach. By integrating clinical information and the results of diagnostic tests, an accurate, validated, and timely diagnosis can be made, while alternative diagnoses can be reasonably excluded. This clinical expert consensus statement reviews the evidence on the management of different CS manifestations and provides advice to practicing clinicians in the field on the role of immunosuppression and the treatment of cardiac complications based on limited published data and the experience of international CS experts. The monitoring and risk stratification of patients with CS is also covered, while controversies and future research needs are explored.

Abstract Cardiac disease affects the heart non-uniformly. Examples include focal septal or apical hypertrophy with reduced strain in hypertrophic cardiomyopathy, replacement fibrosis with akinesia in an infarct-related coronary artery territory, and a pattern of scarring in dilated cardiomyopathy. The detail and versatility of cardiovascular magnetic resonance (CMR) imaging mean it contains a wealth of information imperceptible to the naked eye and not captured by standard global measures. CMR-derived heterogeneity biomarkers could facilitate early diagnosis, better risk stratification, and a more comprehensive prediction of treatment response. Small cohort and case–control studies demonstrate the feasibility of proof-of-concept structural and functional heterogeneity measures. Detailed radiomic analyses of different CMR sequences using open-source software delineate unique voxel patterns as hallmarks of histopathological changes. Meanwhile, measures of dispersion applied to emerging CMR strain sequences describe variable longitudinal, circumferential, and radial function across the myocardium. Two of the most promising heterogeneity measures are the mean absolute deviation of regional standard deviations on native T1 and T2 and the standard deviation of time to maximum regional radial wall motion, termed the tissue synchronization index in a 16-segment left ventricle model. Real-world limitations include the non-standardization of CMR imaging protocols across different centres and the testing of large numbers of radiomic features in small, inadequately powered patient samples. We, therefore, propose a three-step roadmap to benchmark novel heterogeneity biomarkers, including defining normal reference ranges, statistical modelling against diagnosis and outcomes in large epidemiological studies, and finally, comprehensive internal and external validations.

Abstract Aims Left ventricular hypertrophy (LVH) is an established, independent predictor of cardiovascular disease. Indices derived from the electrocardiogram (ECG) have been used to infer the presence of LVH with limited sensitivity. This study aimed to classify LVH defined by cardiovascular magnetic resonance (CMR) imaging using the 12-lead ECG for cost-effective patient stratification. Methods and results We extracted ECG biomarkers with a known physiological association with LVH from the 12-lead ECG of 37 534 participants in the UK Biobank imaging study. Classification models integrating ECG biomarkers and clinical variables were built using logistic regression, support vector machine (SVM) and random forest (RF). The dataset was split into 80% training and 20% test sets for performance evaluation. Ten-fold cross validation was applied with further validation testing performed by separating data based on UK Biobank imaging centres. QRS amplitude and blood pressure (P < 0.001) were the features most strongly associated with LVH. Classification with logistic regression had an accuracy of 81% [sensitivity 70%, specificity 81%, Area under the receiver operator curve (AUC) 0.86], SVM 81% accuracy (sensitivity 72%, specificity 81%, AUC 0.85) and RF 72% accuracy (sensitivity 74%, specificity 72%, AUC 0.83). ECG biomarkers enhanced model performance of all classifiers, compared to using clinical variables alone. Validation testing by UK Biobank imaging centres demonstrated robustness of our models. Conclusion A combination of ECG biomarkers and clinical variables were able to predict LVH defined by CMR. Our findings provide support for the ECG as an inexpensive screening tool to risk stratify patients with LVH as a prelude to advanced imaging.

Background: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features. Methods: UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative. Results: Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes. Conclusions: In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.