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Cardiac sarcoidosis (CS), a rare condition characterized by non-caseating granulomas, can manifest with symptoms such as atrioventricular block and ventricular tachycardia (VT), as well as mimic inherited cardiomyopathies. A 48-year-old male presented with recurrent VT. The initial 18F-fluorodeoxyglucose positron emission tomography (18FDG-PET) scan showed uptake of the mediastinal lymph node. Cardiovascular magnetic resonance (CMR) demonstrated intramyocardial fibrosis. The follow-up 18FDG-PET scan revealed the presence of tracer uptake in the left ventricular (LV) septum, suggesting the likelihood of CS. Genetic testing identified a pathogenic LMNA variant. A 47-year-old female presented with complaints of palpitations and syncope. An Ajmaline provocation test confirmed Brugada syndrome (BrS). CMR revealed signs of cardiac inflammation. An endomyocardial biopsy (EMB) confirmed the diagnosis of cardiac sarcoidosis. Polymorphic VT was induced during an electrophysiological study, and an implantable cardioverter-defibrillator (ICD) was implanted. A 58-year-old woman presented with sustained VT with a prior diagnosis of hypertrophic cardiomyopathy (HCM). A genetic work-up identified the presence of a heterozygous MYBC3 variant of unknown significance (VUS). CMR revealed late gadolinium enhancement (LGE), while the 18FDG-PET scan demonstrated LV tracer uptake. The immunosuppressive therapy was adjusted, and no further VTs were observed. A 28-year-old male athlete with right ventricular dilatation and syncope experienced a cardiac arrest during training. Genetic testing identified a pathogenic mutation in PKP2. The autopsy has confirmed the presence of ACM and a distinctive extracardiac sarcoidosis. Cardiac sarcoidosis and inherited cardiomyopathies may interact in several different ways, altering the clinical presentation. Overlapping pathologies are frequently overlooked. Delayed or incomplete diagnosis risks inadequate treatment. Thus, genetic testing and endomyocardial biopsies should be recommended to obtain a clear diagnosis.

Background: Subpopulations of myocardial c-kitpos cells have the ability to stimulate regeneration in ischemic heart disease by paracrine effects. The left atrial appendage (LAA), which is easy accessible during cardiac surgery, may represent a perfect source for c-kitpos cell extraction for autologous cell therapies in the living human. So far, frequency and distribution of c-kitpos cells in LAA are unknown. Methods: LAAs of patients who underwent cardiac surgery due to coronary artery disease (coronary artery bypass graft, CABG), valvular heart disease or both and of two body donors were examined. Tissue was fixed in 4 % paraformaldehyde, embedded in paraffin, dissected in consecutive sections and stained for c-kitpos cells. In parallel, grade of fibrosis, amount of fat per section and cells positive for mast cell tryptase were examined. Results: We collected 27 LAAs (37.0 % female, mean left ventricular ejection fraction 50.4 %, 63.0 % persistent atrial fibrillation (AF)). Most of the patients underwent combined CABG and valve surgery (51.9 %). C-kitpos cells were detected in 3 different regions: A) Attached to the epicardial fat layer, B) close to vascular structures and C) between cardiomyocytes. C-kitpos cells ranged from 0.05 c-kitpos cells per mm2 to 67.5 c-kitpos cells per mm2. We found no association between number of c-kitpos cells and type of AF, amount of fibrosis or amount of fat. Up to 72 % of c-kitpos cells also showed a positive staining for mast cell tryptase. Conclusion: C-kitpos cells are frequent in LAAs of cardiovascular patients with a rather homogenous distribution throughout the LAA. The LAA can therefore be considered as a source for extraction of a reasonable quantity of autologous cardiac progenitor cells in the living human patient.

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk stratification and quality of care assessment is scarce. We aimed to develop reliable models for mortality prediction in SARI patients utilizing ML algorithms and compare its performances with a classic regression analysis approach. Methods Administrative data (dataset randomly split 75%/25% for model training/testing) from years 2016–2019 of 86 German Helios hospitals was retrospectively analyzed. Inpatient SARI cases were defined by ICD-codes J09-J22. Three ML algorithms were evaluated and its performance compared to generalized linear models (GLM) by computing receiver operating characteristic area under the curve (AUC) and area under the precision-recall curve (AUPRC). Results The dataset contained 241,988 inpatient SARI cases (75 years or older: 49%; male 56.2%). In-hospital mortality was 11.6%. AUC and AUPRC in the testing dataset were 0.83 and 0.372 for GLM, 0.831 and 0.384 for random forest (RF), 0.834 and 0.382 for single layer neural network (NNET) and 0.834 and 0.389 for extreme gradient boosting (XGBoost). Statistical comparison of ROC AUCs revealed a better performance of NNET and XGBoost as compared to GLM. Conclusion ML algorithms for predicting in-hospital mortality were trained and tested on a large real-world administrative dataset of SARI patients and showed good discriminatory performances. Broad application of our models in clinical routine practice can contribute to patients’ risk assessment and quality management.

Cardiac sarcoidosis can mimic any cardiomyopathy in different stages. Noncaseating granulomatous inflammation can be missed, because of the nonhomogeneous distribution in the heart. The current diagnostic criteria show discrepancies and are partly nonspecific and insensitive. Besides the diagnostic pitfalls, there are controversies in the understanding of the causes, genetic and environmental background, and the natural evolution of the disease. Here, we review the current pathophysiological aspects and gaps that are relevant for future cardiac sarcoidosis diagnostics and research.

Abstract Aims Models predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in‐hospital mortality rates in HF cohorts on a population level based on administrative data comparing regression analysis with different machine learning (ML) models. Methods and results Inpatient cases with primary International Statistical Classification of Diseases and Related Health Problems (ICD‐10) encoded discharge diagnosis of HF non‐electively admitted to 86 German Helios hospitals between 1 January 2016 and 31 December 2018 were identified. The dataset was randomly split 75%/25% for model development and testing. Highly unbalanced variables were removed. Four ML algorithms were applied, and all algorithms were tuned using a grid search with multiple repetitions. Model performance was evaluated by computing receiver operating characteristic areas under the curve. In total, 59 125 cases (69.8% aged 75 years or older, 51.9% female) were investigated, and in‐hospital mortality was 6.20%. Areas under the curve of all ML algorithms outperformed regression analysis in the testing dataset with values of 0.829 [95% confidence interval (CI) 0.814–0.843] for logistic regression, 0.875 (95% CI 0.863–0.886) for random forest, 0.882 (95% CI 0.871–0.893) for gradient boosting machine, 0.866 (95% CI 0.854–0.878) for single‐layer neural networks, and 0.882 (95% CI 0.872–0.893) for extreme gradient boosting. Brier scores demonstrated a good calibration especially of the latter three models. Conclusions We introduced reliable models to calculate expected in‐hospital mortality based only on administrative routine data using ML algorithms. A broad application could supplement quality measurement programs and therefore improve future HF patient care.

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany.Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016–2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016–2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression.Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112–2,236 (total 8,717) in the corresponding 2016–2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05–1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07–1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09–1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02–1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood −576) was with a window size of 4 days, i.e., average COVID-19 infections 14–17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12–1.29, P < 0.01).Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016–2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE.

Abstract Background Previous studies have suggested PITX2, KCNN3 and ZFHX3 as atrial fibrillation (AF) susceptibility genes. Single common genetic polymorphisms of those genes have been linked with AF phenotypes and rhythm outcome of AF catheter ablation although their mechanisms remain elusive. New gene-based association tests may help clarifying genotype–phenotype correlations. Therefore, we hypothesized that PITX2, KCNN3 and ZFHX3 associate with left atrial enlargement and persistent AF and subsequently with ablation outcome. Methods and results Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing AF catheter ablation were genotyped for ~1,000,000 SNPs. Gene-based association was investigated using two different gene-based association tests (VEGAS, minSNP). Among the three candidate genes, only ZFHX3 associated with left atrial dilatation and AF recurrence after catheter ablation. Conclusion This study suggests a contribution of ZFHX3 to AF remodeling and response to therapy. Future and larger studies are necessary to replicate and apply these findings with an emphasis on designing AF pathophysiology-based multi-locus risk scores.

Atrial fibrillation (AF) is a multifactorial disease with a strong genetic background. It is assumed that common and rare genetic variants contribute to the progression and recurrence of AF. The pathophysiological impact of those variants, especially when they are synonymous or non-coding, is often elusive and translation into functional experiments is difficult. In this study, we propose a method to go straight from genetic variants to defined gene targets. We focused on 55 genes from calcium signaling and 26 genes from extra cellular matrix ECM–receptor interaction that we found to be associated with the progression and recurrence of AF. These genes were mapped on protein–protein interaction data from three different databases. Based on the concept that central regulators are highly connected with their neighbors, we identified central hub proteins according to random walk analysis derived scores representing interaction grade. Our approach resulted in the identification of EGFR, RYR2, and PRKCA (calcium signaling) and FN1 and LAMA1 (ECM–receptor interaction) which represent promising targets for further functional characterization or pharmaceutical intervention.

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease. Reported prevalence rates vary substantially between 1:500 (0.2%) and 1:3,000 (0.03%), which may be attributed to different study designs and population characteristics. Prevalence data for Germany is not available. Consequently, this study aimed (1) to quantify age- and gender-specific clinically diagnosed HCM prevalence in Germany based on the analysis of health care claims data of > 5 million insurants in 2015, and (2) to analyze temporal prevalence trends from 2011 to 2015.Data were extracted from the InGef (Insitute for Applied Health Research) database, which is an anonymized healthcare claims database with longitudinal data from patients insured in one of approximately 70 German social health insurances (SHIs). Patients were classified as HCM prevalent, if they had at least one verified ambulatory or one hospital main- or secondary discharge diagnosis of HCM (I42.1 or I42.2).In 2015, HCM was prevalent in 4,000 out of 5,490,810 patients (0.07%; 1:1,372). HCM prevalence increased gradually with age from 7.4/100,000 persons (95% CI 5.2-10.1) in 0-9 years old to 298.7/100,000 persons (95% CI 276.4-322.4) in patients > 80 years. In all age categories, men had a numerically higher prevalence than women with significant differences in patients > 30 years. There was a gradual annual prevalence increase from 75.8 (95% CI 75.2-76.4) in 2011 to 84.2 (95% CI 83.5-84.8) in 2015 per 100,000 persons.Overall, prevalence of clinically diagnosed HCM in Germany is lower than in systematic population studies based on echocardiographic diagnosis. Prevalence increased with advancing age and showed a constant yearly rise. Those observations may improve our understanding of the burden of this genetic heart disease on the health care system in Germany, increase the diagnostic awareness among clinicians and shape future screening and management strategies.

Background: PR interval prolongation has recently been shown to associate with advanced left atrial remodeling and atrial fibrillation (AF) recurrence after catheter ablation. While different genome-wide association studies (GWAS) have implicated 13 loci to associate with the PR interval as an AF endophenotype their subsequent associations with AF remodeling and response to catheter ablation are unknown. Here, we perform a gene-based analysis of GWAS data to test the hypothesis that PR interval candidate genes also associate with left atrial remodeling and arrhythmia recurrence following AF catheter ablation.Methods and Results: Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing AF catheter ablation were genotyped for ~1,000,000 SNPs. Gene-based association was investigated using VEGAS (versatile gene-based association study). Among the 13 candidate genes, SLC8A1, MEIS1, ITGA9, SCN5A, and SOX5 associated with the PR interval. Of those, ITGA9 and SOX5 were significantly associated with left atrial low voltage areas and left atrial diameter and subsequently with AF recurrence after radiofrequency catheter ablation.Conclusion: This study suggests contributions of ITGA9 and SOX5 to AF remodeling expressed as PR interval prolongation, low voltage areas and left atrial dilatation and subsequently to response to catheter ablation. Future and larger studies are necessary to replicate and apply these findings with the aim of designing AF pathophysiology-based multi-locus risk scores.

Rare variants of genes encoding the cardiac sodium channel and associated compounds have been linked with atrial fibrillation (AF). Nevertheless, current expert consensus does not support genetic testing in AF, which is in part based on the fact that "there is no therapeutic impact derived from AF genetic test results". However, there are no studies available supporting this recommendation. Consequently, this study analyzed the impact of rare variants affecting the cardiac sodium channel on rhythm outcome of AF catheter ablation.In 137 consecutive patients with lone AF enrolled in the Leipzig Heart Center AF ablation registry, screening for mutations in SCN5A, SCN1B - 4B, CAV3, GPD1L, SNTA1 and MOG1 was performed. We identified 3 rare non-synonymous variants in SCN5A, 5 in SCN1B, 1 in SCN4B, 1 in CAV3, 6 in GPD1L, 3 in SNTA1 and 3 in MOG1 (16%). Variant carriers were otherwise comparable with non-variant carriers. Analysis of AF recurrence rates after radiofrequency AF catheter ablation by serial 7-day Holter ECG monitoring between 3 and 12 months revealed no difference between groups, i.e. 45% in variant carriers vs. 49% in non-variant carriers.Rare variants in genes encoding the cardiac sodium channel and associated compounds are frequently found in lone AF but were not found to impact the outcome of AF catheter ablation. This finding supports current recommendations not to screen for rare variants for the ablation outcome in AF. Nevertheless, it may at least be helpful for understanding AF mechanisms and larger studies are needed to further explore the possible association between genotype and response to AF therapies.

Left atrial enlargement and persistent atrial fibrillation (AF) are well-known predictors for arrhythmia recurrence after AF catheter ablation (LRAF). In this study, by using pathway enrichment analysis of GWAS data, we tested the hypothesis that genetic pathways associated with these phenotypes are also associated with LRAF.Samples from 660 patients with paroxysmal (n = 370) or persistent AF (n = 290) undergoing de-novo AF catheter ablation were genotyped for ~1,000,000 SNPs. SNPs found to be significantly associated with left atrial diameter (LAD) or AF type were used for gene-based association tests in a systematic biological Knowledge-based mining system for Genome-wide Genetic studies (KGG). Associated genes were tested for pathway enrichment using WEB-based Gene SeT AnaLysis Toolkit (WebGestalt), the Gene Annotation Tool to Help Explain Relationships (GATHER) and the databases provided by Kyoto Encyclopedia of Genes and Genomes (KEGG). In a second step, the association of consistently enriched pathways and LRAF was tested.By using sequential 7-day Holter ECGs, LRAF between 3 and 12 months was observed in 48% and was associated with LAD (B = 1.801, 95% CI 0.760-2.841, p = 1.0E-3) and persistent AF (OR = 2.1; 95% CI 1.567-2.931, p = 2.0E-6). WebGestalt (adj. p = 2.7E-22) and GATHER (adj. p = 5.2E-3) identified the calcium signaling pathway (hsa04020) as the only consistently enriched pathway for LAD, while the extracellular matrix (ECM) -receptor interaction pathway (hsa04512) was the only consistently enriched pathway for AF type (adj. p = 2.1E-15 in WebGestalt; adj. p = 9.3E-4 in GATHER). Both calcium signaling (adj. p = 2.2E-17 in WebGestalt; adj. p = 2.9E-2 in GATHER) and ECM-receptor interaction (adj. p = 1.2E-10 in WebGestalt; adj. p = 2.9E-2 in GATHER) were significantly associated with LRAF.Calcium signaling and ECM-receptor interaction pathways are associated with LAD and AF type and, in turn, with LRAF. Future and larger studies are necessary to replicate and apply these findings.

BACKGROUND:Galectin-3 (Gal-3) is an emerging biomarker in heart failure that is involved in fibrosis and inflammation. However, its potential value as a prognostic marker in atrial fibrillation (AF) is unknown. The aim of this study was to assess the impact of AF catheter ablation on Gal-3 and evaluate its prognostic impact for predicting rhythm outcome after catheter ablation. METHODS:Gal-3 was measured at baseline and after 6 months using specific ELISA. AF recurrences were defined as any atrial arrhythmia lasting longer than 30 sec within 6 months after ablation. RESULTS:In 105 AF patients (65% males, age 62±9 years, 52% paroxysmal AF) undergoing catheter ablation, Gal-3 was measured at baseline and after 6 months and compared with an AF-free control cohort (n=14, 50 % males, age 58±11 years). Gal-3 was higher in AF patients compared with AF-free controls (7.8±2.9 vs. 5.8±1.8, ng/mL, p=0.013). However, on multivariable analysis, BMI (p=0.007) but not AF (p=0.068) was associated with Gal-3. In the AF cohort, on univariable analysis higher Gal-3 levels were associated with female gender (p=0.028), higher BMI (p=0.005) and both CHADS2 (p=0.008) and CHA2DS2-VASC (p=0.016) scores, however, on multivariable analysis only BMI remained significantly associated with baseline Gal-3 (p=0.016). Gal-3 was similar 6 months after AF catheter ablation and was not associated with sinus rhythm maintenance. CONCLUSIONS:Although galectin-3 levels are higher in AF patients, this is driven by cardiometabolic co-morbidities and not heart rhythm. Gal-3 is not useful for predicting rhythm outcome of catheter ablation.