Aims: The coronavirus disease 2019 (COVID-19) pandemic has led to changes in health care utilization for different acute cardiovascular diseases. Whether hospitalization rates and in-hospital mortality were affected by the pandemic in patients with acute symptomatic heart failure (HF) was investigated in this study. Methods and results: Administrative data provided by 67 German Helios hospitals were examined for patients with a main discharge diagnosis of HF using ICD codes. Urgent hospital admissions per day were compared for a study period (13 March–21 May 2020) with control intervals in 2020 (1 January–12 March) and 2019 (13 March–21 May), resulting in a total of 13 484 patients excluding all patients with laboratory-proven COVID-19 infection. Incidence rate ratios (IRR) were calculated using Poisson regression. Generalized linear mixed models were used for univariable and multivariable analysis to identify predictors of in-hospital mortality. The number of admissions per day was lower in the study period compared to the same year [IRR 0.69, 95% confidence interval (CI) 0.67–0.73, P < 0.01] and the previous year control group (IRR 0.73, 95% CI 0.70–0.76, P < 0.01). Age was similar throughout the intervals, but case severity increased in terms of distribution within New York Heart Association (NYHA) classes and comorbidities. Within the study period, 30-day rates for urgent hospital readmissions were higher compared to the same year but not the previous year control group. In-hospital mortality was 7.3% in the study period, 6.1% in the same year (P = 0.03) and 6.0% in the previous year control group (P = 0.02). In multivariable analysis, age, NYHA class and other predictors of fatal outcome were identified but hospitalization during the study period was not independently associated with mortality. Conclusion: Our data showed a significant reduction of urgent hospital admissions for HF with increased case severity and concomitant in-hospital mortality during the COVID-19 pandemic in Germany. Identifying causes of reduced inpatient treatment rates is essential for the understanding and valuation with regard to future optimal management of patients with HF.

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.

Aims: The diagnostic application of artificial intelligence (AI)-based models to detect cardiovascular diseases from electrocardiograms (ECGs) evolves, and promising results were reported. However, external validation is not available for all published algorithms. The aim of this study was to validate an existing algorithm for the detection of left ventricular systolic dysfunction (LVSD) from 12-lead ECGs. Methods and results: Patients with digitalized data pairs of 12-lead ECGs and echocardiography (at intervals of ≤7 days) were retrospectively selected from the Heart Center Leipzig ECG and electronic medical records databases. A previously developed AI-based model was applied to ECGs and calculated probabilities for LVSD. The area under the receiver operating characteristic curve (AUROC) was computed overall and in cohorts stratified for baseline and ECG characteristics. Repeated echocardiography studies recorded ≥3 months after index diagnostics were used for follow-up (FU) analysis. At baseline, 42 291 ECG-echocardiography pairs were analysed, and AUROC for LVSD detection was 0.88. Sensitivity and specificity were 82% and 77% for the optimal LVSD probability cut-off based on Youden’s J. AUROCs were lower in ECG subgroups with tachycardia, atrial fibrillation, and wide QRS complexes. In patients without LVSD at baseline and available FU, model-generated high probability for LVSD was associated with a four-fold increased risk of developing LVSD during FU. Conclusion: We provide the external validation of an existing AI-based ECG-analysing model for the detection of LVSD with robust performance metrics. The association of false positive LVSD screenings at baseline with a deterioration of ventricular function during FU deserves a further evaluation in prospective trials.

Aim: Cardiac sympathetic denervation (CSD) has been introduced as a bailout therapy in patients with structural heart disease and refractory ventricular arrhythmias (VAs), but available data are scarce. Purpose of this study was to estimate immediate results, complications, and mid-term outcomes of CSD following recurrent VA after catheter ablation. Methods and results: Adult patients who underwent CSD in the Heart Center Leipzig from March 2017 to February 2021 were retrospectively analysed. Follow-up (FU) was executed via implantable cardioverter defibrillator (ICD) interrogation, telephone interviews, and reviewing medical records. Twenty-one patients (age 63.7 ± 14.4 years, all men, 71.4% non-ischaemic cardiomyopathy, left ventricular ejection fraction 31.6 ± 12.6%) received CSD via video-assisted thoracoscopic surgery (90.5% bilateral, 9.5% left-sided only). Indication for CSD was monomorphic ventricular tachycardia in 76.2% and ventricular fibrillation in 23.8 with 71.4% of patients presenting with electrical storm before index hospitalization. Procedure-related major complications occurred in 9.5% of patients. In-hospital adverse events not related to surgery were common (28.6%) and two patients died during the index hospital stay. During FU (mean duration 9.1 ± 6.5 months), five more patients died. Of the remaining patients, 38.5 and 76.9% were free from any VA or ICD shocks, respectively. Conclusions: The CSD showed additional moderate efficacy to suppress VAs, when performed as a bailout therapy after previously unsuccessful catheter ablation. At 9 months, it was associated with freedom of ICD shocks in two-thirds of patients. In a population with many comorbidities, the rate of CSD-related complications was acceptable, although there was an overall high risk of procedure unrelated adverse events and death.

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.

Left bundle branch area pacing (LBBAP) can be technically challenging and fluoroscopy-intense. Three-dimensional electroanatomical mapping (EAM) facilitates non-fluoroscopic lead navigation and electrogram mapping. We sought to prospectively evaluate the feasibility, safety, and outcomes of routine EAM-guided LBBAP in patients with structural heart disease (SHD) and advanced conduction abnormalities. Consecutive patients with SHD and conduction abnormalities who underwent an attempt at EAM-guided LBBAP were included. The feasibility, safety, procedural, and mid-term outcomes were evaluated. Electrical, echocardiographic, and clinical parameters were assessed at implantation and last follow-up. Thirty-two patients (68 ± 18 years; 19% female) were included, of which 75% had intrinsic QRS > 150 ms, 53% left bundle branch block, and 25% right bundle branch block. Primary EAM-guided LBBAP was successful in 29 patients (91%). The procedural duration was 95 (70–110) min, total fluoroscopy time 0.93 (0.40–1.73) min, and total fluoroscopy dose 35.4 (20.5–77.2) cGy cm2. Paced QRS duration (QRSd) was significantly shorter than intrinsic QRSd (121.9 ± 10.7 vs. 159.2 ± 34.4 ms; P < 0.001) and remained stable during the mean follow-up of 7.0 ± 5.9 months. The LBBAP capture threshold was 0.57 ± 0.23 V/0.4 ms at implantation and remained low during follow-up (0.58 ± 0.18 V/0.5 ± 0.2 ms; P = 0.877). Overall left ventricular ejection fraction improved significantly from 44.2 ± 14.3% at baseline to 49.4 ± 13.1% at follow-up (P = 0.009), New York Heart Association class from 2.4 ± 0.6 to 1.8 ± 0.6 (P = 0.002), respectively. No complications occurred that required intervention. Routine near-zero fluoroscopy EAM-guided LBBAP can safely be performed in patients with SHD and advanced conduction abnormalities with high success rates and favourable mid-term outcomes. Further studies are needed to investigate whether the use of EAM improves the overall outcome of conduction system pacing and to identify specific patient populations who benefit the most from EAM-guided lead implantation.