Corrigendum: Case Report: Four cases of cardiac sarcoidosis in patients with inherited cardiomyopathy-a phenotypic overlap, co-existence of two rare cardiomyopathies or a second-hit disease.

[This corrects the article DOI: 10.3389/fcvm.2023.1328802.].

C-kitpos cells in the human left atrial appendage.

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.

Pathophysiological Gaps, Diagnostic Challenges, and Uncertainties in Cardiac Sarcoidosis.

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.

Case Report: Four cases of cardiac sarcoidosis in patients with inherited cardiomyopathy-a phenotypic overlap, co-existence of two rare cardiomyopathies or a second-hit disease.

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.

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network.

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.

Expected and observed in-hospital mortality in heart failure patients before and during the COVID-19 pandemic: Introduction of the machine learning-based standardized mortality ratio at Helios hospitals.

BACKGROUND: Reduced hospital admission rates for heart failure (HF) and evidence of increased in-hospital mortality were reported during the COVID-19 pandemic. The aim of this study was to apply a machine learning (ML)-based mortality prediction model to examine whether the latter is attributable to differing case mixes and exceeds expected mortality rates. METHODS AND RESULTS: Inpatient cases with a primary discharge diagnosis of HF non-electively admitted to 86 German Helios hospitals between 01/01/2016 and 08/31/2020 were identified. Patients with proven or suspected SARS-CoV-2 infection were excluded. ML-based models were developed, tuned, and tested using cases of 2016-2018 (n = 64,440; randomly split 75%/25%). Extreme gradient boosting showed the best model performance indicated by a receiver operating characteristic area under the curve of 0.882 (95% confidence interval [CI]: 0.872-0.893). The model was applied on data sets of 2019 and 2020 (n = 28,556 cases) and the hospital standardized mortality ratio (HSMR) was computed as the observed to expected death ratio. Observed mortality rates were 5.84% (2019) and 6.21% (2020), HSMRs based on an individual case-based mortality probability were 100.0 (95% CI: 93.3-107.2; p = 1.000) for 2019 and 99.3 (95% CI: 92.5-106.4; p = .850) for 2020. Within subgroups of age or hospital volume, there were no significant differences between observed and expected deaths. When stratified for pandemic phases, no excess death during the COVID-19 pandemic was observed. CONCLUSION: Applying an ML algorithm to calculate expected inpatient mortality based on administrative data, there was no excess death above expected event rates in HF patients during the COVID-19 pandemic.

Hospitalisations for emergency-sensitive conditions in Germany during the COVID-19 pandemic: insights from the German-wide Helios hospital network.

BACKGROUND: While there are numerous reports that describe emergency care during the early COVID-19 pandemic, there is scarcity of data for later stages. This study analyses hospitalisation rates for 37 emergency-sensitive conditions in the largest German-wide hospital network during different pandemic phases. METHODS: Using claims data of 80 hospitals, consecutive cases between 1 January and 17 November 2020 were analysed and compared with a corresponding period in 2019. Incidence rate ratios (IRRs) comparing the two periods were calculated using Poisson regression to model the number of hospitalisations per day. RESULTS: There was a reduction in hospitalisations between 12 March and 13 June 2020 (coinciding with the first pandemic wave) with 32 807 hospitalisations (349.0/day) as opposed to 39 379 (419.0/day) in 2019 (IRR 0.83, 95% CI 0.82 to 0.85, p<0.01). During the following period (14 June-17 November 2020, including the start of second wave), hospitalisations were reduced from 63 799 (406.4/day) in 2019 to 59 910 (381.6/day) in 2020, but this reduction was not as pronounced (IRR 0.94, 95% CI 0.93 to 0.95, p<0.01). During the first wave hospitalisations for acute myocardial infarction, aortic aneurysm/dissection, pneumonitis, paralytic ileus/intestinal obstruction and pulmonary embolism declined but subsequently increased compared with the corresponding periods in 2019. In contrast, hospitalisations for sepsis, pneumonia, obstructive pulmonary disease and intracranial injuries were reduced during the entire observation period. CONCLUSIONS: There was an overall reduction of absolute hospitalisations for emergency-sensitive conditions in Germany during the first 10 months of the COVID-19 pandemic with heterogeneous effects on different disease categories. The increase in hospitalisations for acute myocardial infarction, aortic aneurysm/dissection and pulmonary embolism requires attention and further studies.

Potential Contributors to Increased Pulmonary Embolism Hospitalizations During the COVID-19 Pandemic: Insights From the German-Wide Helios Hospital Network.

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.

Gender differences in patients with structural heart disease undergoing VT ablation.

INTRODUCTION: This study sought to examine gender differences in patients with structural heart disease (SHD) referred for ablation of ventricular tachycardia (VT). BACKGROUND: Female patients are often underrepresented in large studies. Significant differences in the clinical presentation, treatment, and prognosis of female patients have been described in previous studies. METHODS AND RESULTS: We investigated 88 female patients with SHD undergoing VT ablation (mean age 59 years, 56% nonischemic cardiomyopathy, mean left ventricular ejection fraction 35%, 82% in electrical storm). A case-control study with 88 male patients was performed and the results regarding clinical and procedural characteristics, acute and long-term results of the two groups were compared. The female patients had more arrhythmogenic substrate, as they more commonly presented with electrical storm (p = .016) and had a higher number of inducible VT morphologies during the procedure (p = .018). Moreover, the female patients were less likely to have an optimized heart failure medical treatment at baseline (p = .030) and required more time from the first manifestation of the VT to ablation referral (p = .034). Although fewer epicardial ablations were performed in female patients (p = .019), the two groups showed similar results regarding VT noninducibility as ablation endpoint (p = .844), major procedure-related complications (p = .719) and freedom from VT during follow-up (p = .268). Moreover, the overall mortality in the two groups was similar (p = .176). Advanced NYHA class was associated with worse transplant and assist-device-free survival in the female group. CONCLUSION: Female patients presenting for VT ablation had more arrhythmogenic substrate and were less likely to have an optimized heart failure medical treatment. Nevertheless, the procedural acute and long-term outcomes between the two genders were similar.

Anticoagulation in special patient populations with atrial fibrillation.

Anticoagulation in patients with atrial fibrillation (AF) should be guided by considerations of the risk of thromboembolism, stroke, and bleeding as well as the patient's preference. Well-recognized scores have been developed to help the clinician in daily risk assessment, but there are several special patient populations for whom scores are not developed or validated. Furthermore, these patients were not adequately represented in the pivotal randomized trials for non-vitamin K antagonist oral anticoagulants (NOACs). In patients with cancer, the intrinsic hypercoagulable state has to be balanced against an increased risk of bleeding, and a dynamic concept should be applied, taking into account the cancer type, current disease state, therapeutic strategy, and patient-related factors, with NOACs playing an increasingly larger role. In women with planned pregnancy or already pregnant, NOACs should be avoided. However, accidental exposure during pregnancy should not lead to recommendations for pregnancy termination in view of current observational data. Whether patients on dialysis with AF benefit from anticoagulation at all is questionable. But if the decision for anticoagulation is made, NOACs may contribute to a more favorable risk-benefit profile than vitamin- K antagonists. Finally, patients on the ward deserve special considerations regarding periprocedural management of anticoagulation. Although for the majority of procedures a short discontinuation of oral anticoagulation seems appropriate, there are some low-bleeding-risk procedures that do not require cessation. The aim of the present review is to discuss the major particularities of these four patient subgroups and thus to facilitate the clinical decision-making.

Machine ​learning algorithms for claims data-based prediction of in-hospital mortality in patients with heart failure.

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.

Admission rates and care pathways in patients with atrial fibrillation during the COVID-19 pandemic-insights from the German-wide Helios hospital network.

AIMS: Several reports indicate lower rates of emergency admissions in the cardiovascular sector and reduced admissions of patients with chronic diseases during the Coronavirus SARS-CoV-2 (COVID-19) pandemic. The aim of this study was therefore to evaluate numbers of admissions in incident and prevalent atrial fibrillation and flutter (AF) and to analyse care pathways in comparison to 2019. METHODS: A retrospective analysis of claims data of 74 German Helios hospitals was performed to identify consecutive patients hospitalized with a main discharge diagnosis of AF. A study period including the start of the German national protection phase (13 March 2020 to 16 July 2020) was compared to a previous year control cohort (15 March 2019 to 18 July 2019), with further sub-division into early and late phase. Incidence rate ratios (IRRs) were calculated. Numbers of admission per day (A/day) for incident and prevalent AF and care pathways including readmissions, numbers of transesophageal echocardiogram (TEE), electrical cardioversion (CV), and catheter ablation (CA) were analysed. RESULTS: During the COVID-19 pandemic, there was a significant decrease in total AF admissions both in the early (44.4 vs. 77.5 A/day, IRR 0.57 [95% confidence interval (CI) 0.54-0.61], P < 0.01) and late (59.1 vs. 63.5 A/day, IRR 0.93 [95% CI 0.90-0.96], P < 0.01) phases, length of stay was significantly shorter (3.3 ± 3.1 nights vs. 3.5 ± 3.6 nights, P < 0.01), admissions were more frequently in high-volume centres (77.0% vs. 75.4%, P = 0.02), and frequency of readmissions was reduced (21.7% vs. 23.6%, P < 0.01) compared to the previous year. Incident AF admission rates were significantly lower both in the early (21.9 admission per day vs. 41.1 A/day, IRR 0.53 [95% CI 0.48-0.58]) and late (35.5 vs. 39.3 A/day, IRR 0.90 [95% CI 0.86-0.95]) phases, whereas prevalent admissions were only lower in the early phase (22.5 vs. 36.4 A/day IRR 0.62 [95% CI 0.56-0.68]), but not in the late phase (23.6 vs. 24.2 A/day IRR 0.97 [95% CI 0.92-1.03]). Analysis of care pathways showed reduced numbers of TEE during the early phase [34.7% vs. 41.4%, odds ratio (OR) 0.74 [95% CI 0.64-0.86], P < 0.01], but not during the late phase (39.9% vs. 40.2%, OR 0.96 [95% CI 0.88-1.03], P = 0.26). Numbers of CV were comparable during early (40.6% vs. 39.7%, OR 1.08 [95% CI 0.94-1.25], P = 0.27) and late (38.6% vs. 37.5%, OR 1.06 [95% CI 0.98-1.14], P = 0.17) phases, compared to the previous year, respectively. Numbers of CA were comparable during the early phase (21.6% vs. 21.1%, OR 0.98 [95% CI 0.82-1.17], P = 0.82) with a distinct increase during the late phase (22.9% vs. 21.5%, OR 1.05 [95% CI 0.96-1.16], P = 0.28). CONCLUSION: During the COVID-19 pandemic, AF admission rates declined significantly, with a more pronounced reduction in incident than in prevalent AF. Overall AF care was maintained during early and late pandemic phases with only minor changes, namely less frequent use of TEE. Confirmation of these findings in other study populations and identification of underlying causes are required to ensure optimal therapy in patients with AF during the COVID-19 pandemic.

Hospitalization deficit of in- and outpatient cases with cardiovascular diseases and utilization of cardiological interventions during the COVID-19 pandemic: Insights from the German-wide helios hospital network.

BACKGROUND: Treatment numbers of various cardiovascular diseases were reduced throughout the early phase of the ongoing COVID-19 pandemic. Aim of this study was to (a) expand previous study periods to examine the long-term course of hospital admission numbers, (b) provide data for in- and outpatient care pathways, and (c) illustrate changes of numbers of cardiovascular procedures. METHODS AND RESULTS: Administrative data of patients with ICD-10-encoded primary diagnoses of cardiovascular diseases (heart failure, cardiac arrhythmias, ischemic heart disease, valvular heart disease, hypertension, peripheral vascular disease) and in- or outpatient treatment between March, 13th 2020 and September, 10th 2020 were analyzed and compared with 2019 data. Numbers of cardiovascular procedures were calculated using OPS-codes. The cumulative hospital admission deficit (CumAD) was computed as the difference between expected and observed admissions for every week in 2020. In total, 80 hospitals contributed 294 361 patient cases to the database without relevant differences in baseline characteristics between the studied periods. There was a CumAD of -10% to -16% at the end of the study interval in 2020 for all disease groups driven to varying degrees by both reductions of in- and outpatient case numbers. The number of performed interventions was significantly reduced for all examined procedures (catheter ablations: -10%; cardiac electronic device implantations: -7%; percutaneous cardiovascular interventions: -9%; cardiovascular surgery: -15%). CONCLUSIONS: This study provides data on the long-term development of cardiovascular patient care during the COVID-19 pandemic demonstrating a significant CumAD for several cardiovascular diseases and a concomitant performance deficit of cardiovascular interventions.

Genetic Susceptibility for Atrial Fibrillation in Patients Undergoing Atrial Fibrillation Ablation.

BACKGROUND: Ablation is a widely used therapy for atrial fibrillation (AF); however, arrhythmia recurrence and repeat procedures are common. Studies examining surrogate markers of genetic susceptibility to AF, such as family history and individual AF susceptibility alleles, suggest these may be associated with recurrence outcomes. Accordingly, the aim of this study was to test the association between AF genetic susceptibility and recurrence after ablation using a comprehensive polygenic risk score for AF. METHODS: Ten centers from the AF Genetics Consortium identified patients who had undergone de novo AF ablation. AF genetic susceptibility was measured using a previously described polygenic risk score (N=929 single-nucleotide polymorphisms) and tested for an association with clinical characteristics and time-to-recurrence with a 3 month blanking period. Recurrence was defined as >30 seconds of AF, atrial flutter, or atrial tachycardia. Multivariable analysis adjusted for age, sex, height, body mass index, persistent AF, hypertension, coronary disease, left atrial size, left ventricular ejection fraction, and year of ablation. RESULTS: Four thousand two hundred seventy-six patients were eligible for analysis of baseline characteristics and 3259 for recurrence outcomes. The overall arrhythmia recurrence rate between 3 and 12 months was 44% (1443/3259). Patients with higher AF genetic susceptibility were younger (P<0.001) and had fewer clinical risk factors for AF (P=0.001). Persistent AF (hazard ratio [HR], 1.39 [95% CI, 1.22-1.58]; P<0.001), left atrial size (per cm: HR, 1.32 [95% CI, 1.19-1.46]; P<0.001), and left ventricular ejection fraction (per 10%: HR, 0.88 [95% CI, 0.80-0.97]; P=0.008) were associated with increased risk of recurrence. In univariate analysis, higher AF genetic susceptibility trended towards a higher risk of recurrence (HR, 1.08 [95% CI, 0.99-1.18]; P=0.07), which became less significant in multivariable analysis (HR, 1.06 [95% CI, 0.98-1.15]; P=0.13). CONCLUSIONS: Higher AF genetic susceptibility was associated with younger age and fewer clinical risk factors but not recurrence. Arrhythmia recurrence after AF ablation may represent a genetically different phenotype compared to AF susceptibility.

Catheter ablation of ventricular arrhythmias and in-hospital mortality: insights from the German-wide Helios hospital network of 5052 cases.

AIMS: Catheter ablation (CA) of ventricular arrhythmias is one of the most challenging electrophysiological interventions with an increasing use over the last years. Several benefits must be weighed against the risk of potentially life-threatening complications which necessitates a steady reevaluation of safety endpoints. Therefore, the aims of this study were (i) to investigate overall in-hospital mortality in patients undergoing such procedures and (ii) to identify variables associated with in-hospital mortality in a German-wide hospital network. METHODS AND RESULTS: Between January 2010 and September 2018, administrative data provided by 85 Helios hospitals were screened for patients with main or secondary discharge diagnosis of ventricular tachycardia (VT) or premature ventricular contractions (PVCs) in combination with an arrhythmia-related CA using ICD- and OPS codes. In 5052 cases (mean age 60.9 ± 14.3 years, 30.1% female) of 30 different hospitals, in-hospital mortality was 1.27% with a higher mortality in patients ablated for VT (1.99%, n = 2, 955) compared to PVC (0.24%, n = 2, 097, P < 0.01). Mortality rates were 2.06% in patients with ischaemic heart disease (IHD, n = 2, 137), 1.47% in patients with non-ischaemic structural heart disease (NIHD, n = 1, 224), and 0.12% in patients without structural heart disease (NSHD, n = 1, 691). Considering different types of hospital admission, mortality rates were 0.35% after elective (n = 2, 825), 1.60% after emergency admission/hospital transfer <24 h (n = 1, 314) and 3.72% following delayed hospital transfer >24 h after initial admission (n = 861, P < 0.01 vs. elective admission and emergency admission/hospital transfer <24 h). In multivariable analysis, a delayed hospital transfer >24 h [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.59-3.28, P < 0.01], the occurrence of procedure-related major adverse events (OR 6.81, 95% CI 2.90-16.0, P < 0.01), Charlson Comorbidity Index (CCI, OR 2.39, 95% CI 1.56-3.66, P < 0.01) and its components congestive heart failure (OR 8.04, 95% CI 1.71-37.8, P < 0.01), and diabetes mellitus (OR 1.59, 95% CI 1.13-2.22, P < 0.01) were significantly associated with in-hospital death. CONCLUSIONS: We reported in-hospital mortality rates after CA of ventricular arrhythmias in the largest multicentre, administrative dataset in Germany which can be implemented in quality management programs. Aside from comorbidities, a delayed hospital transfer to a CA performing centre is associated with an increased in-hospital mortality. This deserves further studies to determine the optimal management strategy.