[Healthcare 4.0-Medicine in transition]. / Healthcare 4.0 ­ Medizin im Wandel.

Healthcare 4.0 describes the future transformation of the healthcare sector driven by the combination of digital technologies, such as artificial intelligence (AI), big data and the Internet of Medical Things, enabling the advancement of precision medicine. This overview article addresses various areas such as large language models (LLM), diagnostics and robotics, shedding light on the positive aspects of Healthcare 4.0 and showcasing exciting methods and application examples in cardiology. It delves into the broad knowledge base and enormous potential of LLMs, highlighting their immediate benefits as digital assistants or for administrative tasks. In diagnostics, the increasing usefulness of wearables is emphasized and an AI for predicting heart filling pressures based on cardiac magnetic resonance imaging (MRI) is introduced. Additionally, it discusses the revolutionary methodology of a digital simulation of the physical heart (digital twin). Finally, it addresses both regulatory frameworks and a brief vision of data-driven healthcare delivery, explaining the need for investments in technical personnel and infrastructure to achieve a more effective medicine.

Assessing the Applicability of Cardiac Myosin Inhibitors for Hypertrophic Cardiomyopathy Management in a Large Single Center Cohort.

Background: Cardiac myosin inhibitors (CMIs), including Mavacamten and Aficamten, have emerged as a groundbreaking treatment for hypertrophic cardiomyopathy (HCM). The results from phase 2 and 3 randomized clinical trials for both drugs have showed promising outcomes. However, the highly selective patient recruitment for these trials raises questions about the generalizability of the observed positive effects across broader patient populations suffering from HCM. Methods: A retrospective cohort study at University Hospital Heidelberg included 404 HCM patients. Baseline assessments included family history, electrocardiograms (ECGs), and advanced cardiac imaging, to ensure the exclusion of secondary causes of left ventricular hypertrophy. Results: Among the HCM patients evaluated, only a small percentage met the inclusion criteria for recent CMI trials: 10.4% for EXPLORER-HCM and 4.7% for SEQUOIA-HCM. The predominant exclusion factor was the stringent left ventricular outflow tract (LVOT) gradient requirement. Conclusions: This study highlights a significant discrepancy between patient demographics in clinical trials and those encountered in routine HCM clinical practice. Despite promising results from the initial randomized clinical trials that led to the approval of Mavacamten, the selected patient population only represents a small part of the HCM patient cohort seen in routine clinics. This study advocates for further expanded randomized clinical trials with broader inclusion criteria to represent diverse primary HCM patient populations.

Integrative Analyses of Circulating Proteins and Metabolites Reveal Sex Differences in the Associations with Cardiac Function among DCM Patients.

Dilated cardiomyopathy (DCM) is characterized by reduced left ventricular ejection fraction (LVEF) and left or biventricular dilatation. We evaluated sex-specific associations of circulating proteins and metabolites with structural and functional heart parameters in DCM. Plasma samples (297 men, 71 women) were analyzed for proteins using Olink assays (targeted analysis) or LC-MS/MS (untargeted analysis), and for metabolites using LC MS/MS (Biocrates AbsoluteIDQ p180 Kit). Associations of proteins (n = 571) or metabolites (n = 163) with LVEF, measured left ventricular end diastolic diameter (LVEDDmeasured), and the dilation percentage of LVEDD from the norm (LVEDDacc. to HENRY) were examined in combined and sex-specific regression models. To disclose protein-metabolite relations, correlation analyses were performed. Associations between proteins, metabolites and LVEF were restricted to men, while associations with LVEDD were absent in both sexes. Significant metabolites were validated in a second independent DCM cohort (93 men). Integrative analyses demonstrated close relations between altered proteins and metabolites involved in lipid metabolism, inflammation, and endothelial dysfunction with declining LVEF, with kynurenine as the most prominent finding. In DCM, the loss of cardiac function was reflected by circulating proteins and metabolites with sex-specific differences. Our integrative approach demonstrated that concurrently assessing specific proteins and metabolites might help us to gain insights into the alterations associated with DCM.

Interpretation of elevated baseline concentrations and serial changes of high-sensitivity cardiac troponin T in confirmed muscular dystrophies.

AIMS: Concentrations of high-sensitivity cardiac troponin T (hs-cTnT) are frequently elevated in stable patients with confirmed muscle dystrophies. However, sparse information is available on the interpretation of serial concentration changes. METHODS: Hs-cTnT was collected in 35 stable outpatients with confirmed skeletal muscle dystrophies at 0 and 1 h and after 6-12 months during scheduled outpatient visits. We simulated the effectiveness of the European Society of Cardiology (ESC) 0/1 h algorithm and assessed biological variation at 6-12 months using two established methods: reference change value (RCV) and minimal important difference (MID). RESULTS: Median baseline hs-cTnT concentrations were 34.4 ng/L [inter-quartile range (IQR): 17.5-46.2], and values > 99th percentile upper limit of normal were present in 34 of 35 patients. All patients were stable without cardiovascular adverse events during a follow-up of 6.6 months (IQR: 6-7). Median concentration change was 1.9 ng/L (IQR: 0.7-3.2) and 0.8 ng/L (IQR: 0-7.0) at 60 min and 6-9 months, respectively. Applying the criteria of the ESC 0/1 h algorithm for triage of suspected acute coronary syndrome (ACS) showed poor overall effectiveness of baseline hs-cTnT values. No patient would qualify for rule-out based on hs-cTnT less than the limit of detection, whereas five cases would qualify for rule-in based on hs-cTnT ≥ 52 ng/L. Biological variabilities at 6-12 months per MID and RCV were 1.2 ng/L [95% confidence interval (CI): 0.7-2.1] and 28.6% (95% CI: 27.9-29.6), respectively. A total of 8 (22.9%) and 25 (71.4%) cases exceeded the biological variation range, suggesting some additional myocardial damage. CONCLUSIONS: The high prevalence of elevated hs-cTnT could negatively impact the effectiveness of rule-out and rule-in strategies based on a single hs-cTnT value. Knowledge of the physiological and biological variation of hs-cTnT after 6-12 months is helpful to detect the progression of cardiac involvement or to search for cardiac complications including but not limited to arrhythmias that may trigger acute or chronic myocardial damage.

Personalized care in dilated cardiomyopathy: Rationale and study design of the activeDCM trial.

BACKGROUND: Dilated cardiomyopathy (DCM) is a leading cause of heart failure, particularly in younger individuals. Low physical strength is a global risk factor for cardiovascular mortality, and physical activity and a healthy lifestyle have been shown to improve outcomes in patients with heart failure. However, inappropriate exercise may increase the risk of arrhythmias in certain individuals with DCM. The determinants for predicting individual risks in this setting are poorly understood, and clinicians are hesitant to recommend sports for cardiomyopathy patients. The activeDCM trial aims to assess the safety and efficacy of a personalized exercise and activity programme for individuals with DCM. STUDY DESIGN: The activeDCM trial is a prospective, randomized, interventional trial with a 12 month follow-up. Three hundred patients, aged 18-75 years with DCM, left ventricular ejection fraction (LVEF) ≤ 50% and New York Heart Association (NYHA) classes I-III, will be enrolled. The intervention includes a personalized exercise and activity programme. The primary outcome is the increase in peak oxygen uptake (VO2max, mL/kg/min) from baseline to 12 months. Secondary endpoints include adherence to personalized activity programmes, freedom from clinically relevant arrhythmia, unplanned hospitalization for heart failure and changes in NYHA class, quality of life scores, 6 min walk distance, muscular strength, N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) levels and cardiac function. Advanced research questions include high-density phenome and omics analysis combined with digital biomarkers derived from Apple Watch devices. DISCUSSION: The activeDCM trial will provide valuable insights into the safety and efficacy of personalized exercise training in DCM patients, inform clinical practice and contribute to the development of heart failure management programmes. The study will generate data on the impact of exercise on various aspects of cardiovascular disease, including genetic, metabolic, phenotypic and longitudinal aspects, facilitating the development of future digital tools and strategies, including the incorporation of smart wearable devices.

Human Genetics of Ebstein Anomaly.

Ebstein anomaly (EA) is a rare, congenital cardiac defect of the tricuspid valve with a birth prevalence between 0.5 and 1 in 20,000 [1]. It is characterized by displacement of the tricuspid valve toward the apex of the right ventricle (RV) and "atrialization" of the RV (Fig. 57.1) [2]. EA accounts for about 0.5% of all congenital heart diseases (CHD) [2]. Depending on severity of the defect and due to heterogeneity of the disease, patient's presentation varies from severe heart failure symptoms and arrhythmia in neonatal life to asymptomatic adults.

Comparative Assessment of Percutaneous Left-Atrial Appendage Occlusion (LAAO) Devices-A Single Center Cohort Study.

BACKGROUND: Percutaneous left-atrial appendage closure (LAAC) is an established method for preventing strokes in patients with atrial fibrillation, offering an alternative to oral anticoagulation. Various occluder devices have been developed to cater to individual anatomical needs and ensure a safe and effective procedure. In this retrospective, monocentric cohort study, we compare different LAAO devices with respect to clinical outcomes, LAA sealing properties, and device-related complications. METHODS: We conducted a retrospective analysis of 270 patients who underwent percutaneous LAA closure in our center between 2009 and 2023. Patient data were extracted from medical records, including gender, age at implantation, indication, device type and size, laboratory values, LAA anatomy, periprocedural complications, ECG parameters, transthoracic and transesophageal echocardiography parameters (TTE and TEE), as well as medication at discharge. Moreover, fluoroscopy time and implantation duration, as well as post-implantation clinical events up to 1 year, were collected. Endpoints were bleeding events, recurrent stroke, thrombi on devices, and death. RESULTS: The implanted devices were the Watchman 2.5, Watchman FLX, Amplatzer Cardiac Plug (ACP), and Amulet. The procedural success rate was 95.7% (n = 265), with cactus anatomy posing the most challenges across all devices. The mean patient age was 75.5 ± 7.7 years, with 64.5% being male. The median CHA2DS2-VASc score was 4.8 ± 1.5 and the median HAS-BLED score was 3.8 ± 1.0. Indications for LAA closure included past bleeding events and elevated bleeding risk. Periprocedural complications were most commonly bleeding at the puncture site, particularly after ACP implantation (p = 0.014). Significant peridevice leaks (PDL) were observed in 21.4% of simple sealing mechanism devices versus 0% in double sealing mechanism devices (p = 0.004). Thrombi were detected on devices in six patients, with no subsequent ischemic stroke or thromboembolic event. Comparative analysis revealed no significant differences in the occurrence of stroke, transient ischemic attack (TIA), thromboembolic events, device-related thrombi, or mortality among different device types. A 62.3% relative risk reduction in thromboembolic events and 38.6% in major bleedings could be observed over 568.2 patient years. CONCLUSIONS: In summary, our study highlights the efficacy and safety of LAA closure using various occluder devices despite anatomical challenges. Our long-term follow-up findings support LAA closure as a promising option for stroke prevention in selected patient cohorts. Further research is needed to refine patient selection criteria and optimize outcomes in LAA closure procedures.

Prognostic relevance of global work index and global constructive work in patients with non-ischemic dilated cardiomyopathy.

Myocardial work (MW) derived from pressure-strain loops is a novel non-invasive tool to assess left ventricular (LV) function, incorporating global longitudinal strain (GLS) by speckle tracking echocardiography and non-invasively assessed blood pressure. Studies on the role of MW in dilated cardiomyopathy (DCM) are still limited. Therefore, the aim of this study was to evaluate the potential value of MW for predicting adverse outcomes in patients with DCM. 116 consecutive patients with DCM who underwent heart catheterization were retrospectively recruited from June 2009 to July 2014. 34 patients (30%) met the composite endpoints for major adverse cardiac events (MACE) of cardiac transplantation, need for implantable cardioverter-defibrillator (ICD) therapy, heart failure hospitalization and all-cause mortality. Patients with DCM were followed up for a mean of 5.1 years (IQR: 2.2-9.1 years). Global work index (GWI) and global constructive work (GCW) were not only independent predictors but also provided incremental predictive values (Integrated discrimination improvement [IDI] > 0) of MACE in multivariate Cox models. Furthermore, Patients with GWI < 788 mm Hg% (HR 5.46, 95%CI 1.66-17.92, p = 0.005) and GCW < 1,238 mm Hg% (HR 4.46, 95%CI 1.53-12.98, p = 0.006) had higher risks of MACE. GWI and GCW assessed by strain imaging echocardiography may have an additional value beyond LV-EF and GLS for predicting adverse outcomes in DCM.

Prediction of diagnosis and diastolic filling pressure by AI-enhanced cardiac MRI: a modelling study of hospital data.

BACKGROUND: With increasing numbers of patients and novel drugs for distinct causes of systolic and diastolic heart failure, automated assessment of cardiac function is important. We aimed to provide a non-invasive method to predict diagnosis of patients undergoing cardiac MRI (cMRI) and to obtain left ventricular end-diastolic pressure (LVEDP). METHODS: For this modelling study, patients who had undergone cardiac catheterisation at University Hospital Heidelberg (Heidelberg, Germany) between July 15, 2004 and March 16, 2023, were identified, as were individual left ventricular pressure measurements. We used existing patient data from routine cardiac diagnostics. From this initial group, we extracted patients who had been diagnosed with ischaemic cardiomyopathy, dilated cardiomyopathy, hypertrophic cardiomyopathy, or amyloidosis, as well as control individuals with no structural phenotype. Data were pseudonymised and only processed within the university hospital's AI infrastructure. We used the data to build different models to predict either demographic (ie, AI-age and AI-sex), diagnostic (ie, AI-coronary artery disease and AI-cardiomyopathy [AI-CMP]), or functional parameters (ie, AI-LVEDP). We randomly divided our datasets via computer into training, validation, and test datasets. AI-CMP was not compared with other models, but was validated in a prospective setting. Benchmarking was also done. FINDINGS: 66 936 patients who had undergone cardiac catheterisation at University Hospital Heidelberg were identified, with more than 183 772 individual left ventricular pressure measurements. We extracted 4390 patients from this initial group, of whom 1131 (25·8%) had been diagnosed with ischaemic cardiomyopathy, 1064 (24·2%) had been diagnosed with dilated cardiomyopathy, 816 (18·6%) had been diagnosed with hypertrophic cardiomyopathy, 202 (4·6%) had been diagnosed with amyloidosis, and 1177 (26·7%) were control individuals with no structural phenotype. The core cohort only included patients with cardiac catherisation and cMRI within 30 days, and emergency cases were excluded. AI-sex was able to predict patient sex with areas under the receiver operating characteristic curves (AUCs) of 0·78 (95% CI 0·77-0·78) and AI-age was able to predict patient age with a mean absolute error of 7·86 years (7·77-7·95), with a Pearson correlation of 0·57 (95% CI 0·56-0·57). The AUCs for the classification tasks ranged between 0·82 (95% CI 0·79-0·84) for ischaemic cardiomyopathy and 0·92 (0·91-0·94) for hypertrophic cardiomyopathy. INTERPRETATION: Our AI models could be easily integrated into clinical practice and provide added value to the information content of cMRI, allowing for disease classification and prediction of diastolic function. FUNDING: Informatics for Life initiative of the Klaus-Tschira Foundation, German Center for Cardiovascular Research, eCardiology section of the German Cardiac Society, and AI Health Innovation Cluster Heidelberg.

The role of coronary artery disease in lung transplantation: a propensity-matched analysis.

BACKGROUND AND AIMS: Candidate selection for lung transplantation (LuTx) is pivotal to ensure individual patient benefit as well as optimal donor organ allocation. The impact of coronary artery disease (CAD) on post-transplant outcomes remains controversial. We provide comprehensive data on the relevance of CAD for short- and long-term outcomes following LuTx and identify risk factors for mortality. METHODS: We retrospectively analyzed all adult patients (≥ 18 years) undergoing primary and isolated LuTx between January 2000 and August 2021 at the LMU University Hospital transplant center. Using 1:1 propensity score matching, 98 corresponding pairs of LuTx patients with and without relevant CAD were identified. RESULTS: Among 1,003 patients having undergone LuTx, 104 (10.4%) had relevant CAD at baseline. There were no significant differences in in-hospital mortality (8.2% vs. 8.2%, p > 0.999) as well as overall survival (HR 0.90, 95%CI [0.61, 1.32], p = 0.800) between matched CAD and non-CAD patients. Similarly, cardiovascular events such as myocardial infarction (7.1% CAD vs. 2.0% non-CAD, p = 0.170), revascularization by percutaneous coronary intervention (5.1% vs. 1.0%, p = 0.212), and stroke (2.0% vs. 6.1%, p = 0.279), did not differ statistically between both matched groups. 7.1% in the CAD group and 2.0% in the non-CAD group (p = 0.078) died from cardiovascular causes. Cox regression analysis identified age at transplantation (HR 1.02, 95%CI [1.01, 1.04], p < 0.001), elevated bilirubin (HR 1.33, 95%CI [1.15, 1.54], p < 0.001), obstructive lung disease (HR 1.43, 95%CI [1.01, 2.02], p = 0.041), decreased forced vital capacity (HR 0.99, 95%CI [0.99, 1.00], p = 0.042), necessity of reoperation (HR 3.51, 95%CI [2.97, 4.14], p < 0.001) and early transplantation time (HR 0.97, 95%CI [0.95, 0.99], p = 0.001) as risk factors for all-cause mortality, but not relevant CAD (HR 0.96, 95%CI [0.71, 1.29], p = 0.788). Double lung transplant was associated with lower all-cause mortality (HR 0.65, 95%CI [0.52, 0.80], p < 0.001), but higher in-hospital mortality (OR 2.04, 95%CI [1.04, 4.01], p = 0.039). CONCLUSION: In this cohort, relevant CAD was not associated with worse outcomes and should therefore not be considered a contraindication for LuTx. Nonetheless, cardiovascular events in CAD patients highlight the necessity of control of cardiovascular risk factors and a structured cardiac follow-up.

Scrutinizing the Role of Venoarterial Extracorporeal Membrane Oxygenation: Has Clinical Practice Outpaced the Evidence?

The use of venoarterial extracorporeal membrane oxygenation (VA-ECMO) for temporary mechanical circulatory support in various clinical scenarios has been increasing consistently, despite the lack of sufficient evidence regarding its benefit and safety from adequately powered randomized controlled trials. Although the ARREST trial (Advanced Reperfusion Strategies for Patients with Out-of-Hospital Cardiac Arrest and Refractory Ventricular Fibrillation) and a secondary analysis of the PRAGUE OHCA trial (Prague Out-of-Hospital Cardiac Arrest) provided some evidence in favor of VA-ECMO in the setting of out-of-hospital cardiac arrest, the INCEPTION trial (Early Initiation of Extracorporeal Life Support in Refractory Out-of-Hospital Cardiac Arrest) has not found a relevant improvement of short-term mortality with extracorporeal cardiopulmonary resuscitation. In addition, the results of the recently published ECLS-SHOCK trial (Extracorporeal Life Support in Cardiogenic Shock) and ECMO-CS trial (Extracorporeal Membrane Oxygenation in the Therapy of Cardiogenic Shock) discourage the routine use of VA-ECMO in patients with infarct-related cardiogenic shock. Ongoing clinical trials (ANCHOR [Assessment of ECMO in Acute Myocardial Infarction Cardiogenic Shock, NCT04184635], REVERSE [Impella CP With VA ECMO for Cardiogenic Shock, NCT03431467], UNLOAD ECMO [Left Ventricular Unloading to Improve Outcome in Cardiogenic Shock Patients on VA-ECMO, NCT05577195], PIONEER [Hemodynamic Support With ECMO and IABP in Elective Complex High-risk PCI, NCT04045873]) may clarify the usefulness of VA-ECMO in specific patient subpopulations and the efficacy of combined mechanical circulatory support strategies. Pending further data to refine patient selection and management recommendations for VA-ECMO, it remains uncertain whether the present usage of this device improves outcomes.

A contemporary training concept in critical care cardiology.

Critical care cardiology (CCC) in the modern era is shaped by a multitude of innovative treatment options and an increasingly complex, ageing patient population. Generating high-quality evidence for novel interventions and devices in an intensive care setting is exceptionally challenging. As a result, formulating the best possible therapeutic approach continues to rely predominantly on expert opinion and local standard operating procedures. Fostering the full potential of CCC and the maturation of the next generation of decision-makers in this field calls for an updated training concept, that encompasses the extensive knowledge and skills required to care for critically ill cardiac patients while remaining adaptable to the trainee's individual career planning and existing educational programs. In the present manuscript, we suggest a standardized training phase in preparation of the first ICU rotation, propose a modular CCC core curriculum, and outline how training components could be conceptualized within three sub-specialization tracks for aspiring cardiac intensivists.

Improving sudden cardiac death risk stratification in hypertrophic cardiomyopathy using established clinical variables and genetic information.

BACKGROUND AND AIMS: The cardiac societies of Europe and the United States have established different risk models for preventing sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). The aim of this study is to validate current SCD risk prediction methods in a German HCM cohort and to improve them by the addition of genotype information. METHODS: HCM patients without prior SCD or equivalent arrhythmic events ≥ 18 years of age were enrolled in an expert cardiomyopathy center in Germany. The primary endpoint was defined as SCD/-equivalent within 5 years of baseline evaluation. 5-year SCD-risk estimates and recommendations for ICD implantations, as defined by the ESC and AHA/ACC guidelines, were analyzed. Multivariate cox proportional hazards analyses were integrated with genetic findings as additive SCD risk. RESULTS: 283 patients were included and followed for in median 5.77 years (2.92; 8.85). A disease-causing variant was found in 138 (49%) patients. 14 (5%) patients reached the SCD endpoint (5-year incidence 4.9%). Kaplan-Meier survival analysis shows significantly lower overall SCD event-free survival for patients with an identified disease-causing variant (p < 0.05). The ESC HCM Risk-SCD model showed an area-under-the-curve (AUC) of 0.74 (95% CI 0.68-0.79; p < 0.0001) with a sensitivity of 0.29 (95% CI 0.08-0.58) and specificity of 0.83 (95% CI 0.78-0.88) for a risk estimate ≥ 6%/5-years. By comparison, the AHA/ACC HCM SCD risk stratification model showed an AUC of 0.70 (95% CI 0.65-0.76; p = 0.003) with a sensitivity of 0.93 (95% CI, 0.66-0.998) and specificity of 0.28 (95% CI 0.23-0.34) at the respective cut-off. The modified SCD Risk Score with genetic information yielded an AUC of 0.76 (95% CI 0.71-0.81; p < 0.0001) with a sensitivity of 0.86 (95% CI 0.57-0.98) and specificity of 0.69 (95% CI 0.63-0.74). The number-needed-to-treat (NNT) to prevent 1 SCD event by prophylactic ICD-implantation is 13 for the ESC model, 28 for AHA/ACC and 9 for the modified Genotype-model. CONCLUSION: This study confirms the performance of current risk models in clinical decision making. The integration of genetic findings into current SCD risk stratification methods seem feasible and can add in decision making, especially in borderline risk-groups. A subgroup of patients with high SCD risk remains unidentified by current risk scores.

The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary.

The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.

Genetic architecture of cardiac dynamic flow volumes.

Cardiac blood flow is a critical determinant of human health. However, the definition of its genetic architecture is limited by the technical challenge of capturing dynamic flow volumes from cardiac imaging at scale. We present DeepFlow, a deep-learning system to extract cardiac flow and volumes from phase-contrast cardiac magnetic resonance imaging. A mixed-linear model applied to 37,653 individuals from the UK Biobank reveals genome-wide significant associations across cardiac dynamic flow volumes spanning from aortic forward velocity to aortic regurgitation fraction. Mendelian randomization reveals a causal role for aortic root size in aortic valve regurgitation. Among the most significant contributing variants, localizing genes (near ELN, PRDM6 and ADAMTS7) are implicated in connective tissue and blood pressure pathways. Here we show that DeepFlow cardiac flow phenotyping at scale, combined with genotyping data, reinforces the contribution of connective tissue genes, blood pressure and root size to aortic valve function.

Generation of an RBM20-mutation-associated left-ventricular non-compaction cardiomyopathy iPSC line (UMGi255-A) into a DCM genetic background to investigate monogenetic cardiomyopathies.

RBM20 mutations account for 3 % of genetic cardiomypathies and manifest with high penetrance and arrhythmogenic effects. Numerous mutations in the conserved RS domain have been described as causing dilated cardiomyopathy (DCM), whereas a particular mutation (p.R634L) drives development of a different cardiac phenotype: left-ventricular non-compaction cardiomyopathy. We generated a mutation-induced pluripotent stem cell (iPSC) line in which the RBM20-LVNC mutation p.R634L was introduced into a DCM patient line with rescued RBM20-p.R634W mutation. These DCM-634L-iPSC can be differentiated into functional cardiomyocytes to test whether this RBM20 mutation induces development of the LVNC phenotype within the genetic context of a DCM patient.

Insulin resistance in Takotsubo syndrome.

AIMS: Takotsubo syndrome (TTS) is an acute heart failure (AHF) syndrome mimicking the symptoms of acute myocardial infarction. Impaired outcome has been shown, making risk stratification and novel therapeutic concepts a necessity. We hypothesized insulin resistance with elevated plasma glucose and potentially myocardial glucose deprivation to contribute to the pathogenesis of TTS and investigated the therapeutic benefit of insulin in vivo. METHODS AND RESULTS: First, we retrospectively analysed patient data of n = 265 TTS cases (85.7% female, mean age 71.1 ± 14.1 years) with documented initial plasma glucose from the Department of Cardiology of the University Hospital Heidelberg in Germany (May 2011 to May 2021). Median split of the study population according to glucose levels (≤123 mg/dL vs. >123 mg/dL) yielded significantly elevated mean heart rate (80.75 ± 18.96 vs. 90.01 ± 22.19 b.p.m., P < 0.001), left ventricular end-diastolic pressure (LVEDP, 18.51 ± 8.35 vs. 23.09 ± 7.97 mmHg, P < 0.001), C-reactive protein (26.14 ± 43.30 vs. 46.4 ± 68.6 mg/L, P = 0.006), leukocyte count (10.12 ± 4.29 vs. 15.05 ± 9.83/nL, P < 0.001), peak high-sensitive Troponin T (hs-TnT, 515.44 ± 672.15 vs. 711.40 ± 736.37 pg/mL, P = 0.005), reduced left ventricular ejection fraction (EF, 34.92 ± 8.94 vs. 31.35 ± 8.06%, P < 0.001), and elevated intrahospital mortality (2.3% vs. 12.1%, P = 0.002) in the high-glucose group (Student's t-test, Mann-Whitney U test, or chi-squared test). Linear regression indicated a significant association of glucose with HR (P < 0.001), LVEDP (P = 0.014), hs-TnT kinetics from admission to the next day (P < 0.001), hs-TnT the day after admission (P < 0.001), as well as peak hsTnT (P < 0.001). Logistic regression revealed significant association of glucose with a composite intrahospital outcome including catecholamine use, respiratory support, and resuscitation [OR 1.010 (1.004-1.015), P = 0.001]. To further investigate the potential role of glucose in TTS pathophysiology experimentally, we utilized an in vivo murine model of epinephrine (EPI)-driven reversible AHF. For this, male mice underwent therapeutic injection of insulin (INS, 1 IU/kg) or/and glucose (GLU, 0.5 g/kg) after EPI (2.5 mg/kg), both of which markedly improved mean EF (EPI 34.3% vs. EPI + INS + GLU 43.7%, P = 0.025) and significantly blunted mean hs-TnT (EPI 14 393 pg/mL vs. EPI + INS 6864 pg/mL at 24 h, P = 0.039). Particularly, insulin additionally ameliorated myocardial pro-inflammatory gene expression, suggesting an anti-inflammatory effect of acute insulin therapy. CONCLUSIONS: Elevated initial plasma glucose was associated with adverse outcome-relevant parameters in TTS and may present a surrogate parameter of heightened catecholaminergic drive. In mice, insulin- and glucose injection both improved EPI-induced AHF and myocardial damage, indicating insulin resistance rather than detrimental effects of hyperglycaemia itself as the underlying cause. Future studies will investigate the role of HbA1c as a risk stratifier and of insulin-based therapy in TTS.

Mislocalization of pathogenic RBM20 variants in dilated cardiomyopathy is caused by loss-of-interaction with Transportin-3.

Severe forms of dilated cardiomyopathy (DCM) are associated with point mutations in the alternative splicing regulator RBM20 that are frequently located in the arginine/serine-rich domain (RS-domain). Such mutations can cause defective splicing and cytoplasmic mislocalization, which leads to the formation of detrimental cytoplasmic granules. Successful development of personalized therapies requires identifying the direct mechanisms of pathogenic RBM20 variants. Here, we decipher the molecular mechanism of RBM20 mislocalization and its specific role in DCM pathogenesis. We demonstrate that mislocalized RBM20 RS-domain variants retain their splice regulatory activity, which reveals that aberrant cellular localization is the main driver of their pathological phenotype. A genome-wide CRISPR knockout screen combined with image-enabled cell sorting identified Transportin-3 (TNPO3) as the main nuclear importer of RBM20. We show that the direct RBM20-TNPO3 interaction involves the RS-domain, and is disrupted by pathogenic variants. Relocalization of pathogenic RBM20 variants to the nucleus restores alternative splicing and dissolves cytoplasmic granules in cell culture and animal models. These findings provide proof-of-principle for developing therapeutic strategies to restore RBM20's nuclear localization in RBM20-DCM patients.

Machine learning-based prediction of in-hospital death for patients with takotsubo syndrome: The InterTAK-ML model.

AIMS: Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. METHODS AND RESULTS: A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85-0.92), a sensitivity of 0.85 (0.78-0.95) and a specificity of 0.76 (0.74-0.79) in the internal validation cohort and an AUC of 0.82 (0.73-0.91), a sensitivity of 0.74 (0.61-0.87) and a specificity of 0.79 (0.77-0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. CONCLUSION: A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.