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Abstract A precise quantification of mitral regurgitation (MR) severity is essential for treatment and outcome of patients with MR. 3D echocardiography facilitates estimation of MR but selection of patients with necessity of invasive treatment remains challenging. We investigate effective regurgitation orifice area (EROA) quantification by 3D compared to 2D echocardiography in patients with MR and highlight the improved discrimination of MR severity. We consecutively enrolled fifty patients with primary or secondary and at least moderate MR undergoing 2D and 3D colour Doppler echocardiography prior to transcatheter edge-to-edge repair (TEER). Improved accuracy of MR grading using 3D vena contracta area (VCA) as an estimate of EROA was compared to 2D proximal isovelocity surface area (PISA) quantification method and a multiparameter reference standard. Quantification of EROA remarkably varies between 2D and 3D echocardiography and the discrimination between moderate and severe MR was significantly (p = 0.001) different using 2D PISA or 3D VCA, respectively. 3D VCA correlated significantly (r = 0.501, p

Abstract Background Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner. Methods We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples. Results We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920–0.952, p

In a recent untargeted clinical lipidomics study of platelets of coronary artery disease (CAD) patients, medium-chain phosphatidylcholines (MCPCs) with C8 and C10 fatty acyl residues were found significantly upregulated in the patient group with acute coronary syndrome (ACS) as compared to chronic coronary syndrome (CCS) and healthy controls. To support this finding, this work presents the development and optimization of a targeted UHPLC-QTrap-MS/MS method with multiple reaction monitoring acquisition for the quantitative analysis of MCPCs (PC 10:0/8:0, PC 16:0/8:0, PC 10:0/20:4 and PC 10:0/10:0) in platelets for biomarker validation. A systematic optimization of chromatographic and mass spectrometric parameters was performed. A charged surface hybrid CSH C18 (1.7 µm, 130 Å) column and fine-tuned gradient elution with 2-propanol/acetonitrile and ammonium acetate as additive to the mobile phase was employed in the final method in ESI negative mode. Four selected PC standards (PC 6:0/6:0, PC 8:0/8:0, PC 10:0/10:0 and PC 12:0/12:0), which cover well the carbon and retention rime range of the target analytes, were used for the optimization process and calibration. Quantification was based on matrix-matched calibration with these four selected commercially available MCPC standards as surrogate calibrants and PC 6:0/6:0(d22) as internal standard. Furthermore, an organic solvent and fatty acyl carbon number-corrected response factor approach gave also accuracies within acceptance limits of bioanalytical validation guidelines and has more generic applicability. Compared to the previous untargeted RPLC-ESI-QTOF-MS/MS method, the optimized targeted UHPLC-QTrap-MS/MS assay showed increased sensitivity and selectivity for the detection of medium-chain PCs in platelet samples of CAD (LOQs in the range of 0.5–5 nmol/L). The method performance parameters indicated its suitability for a future biomarker validation study of MCPCs in platelets.

Abstract Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use of high sensitivity troponin essays remains a critical challenge in emergency medicine. We enrolled 2760 patients (average age 70 years, 58.6% male) with chest pain and suspected ACS, who were admitted to the Emergency Department of the University Hospital Tübingen, Germany, between August 2016 and October 2020. Using 26 features, eight Machine learning models (non-deep learning models) were trained with data from the preclinical rescue protocol and compared to the “TropOut” score (a modified version of the “preHEART” score which consists of history, ECG, age and cardiac risk but without troponin analysis) to predict major adverse cardiac event (MACE) and acute coronary artery occlusion (ACAO). In our study population MACE occurred in 823 (29.8%) patients and ACAO occurred in 480 patients (17.4%). Interestingly, we found that all machine learning models outperformed the “TropOut” score. The VC and the LR models showed the highest area under the receiver operating characteristic (AUROC) for predicting MACE (AUROC = 0.78) and the VC showed the highest AUROC for predicting ACAO (AUROC = 0.81). A SHapley Additive exPlanations (SHAP) analyses based on the XGB model showed that presence of ST-elevations in the electrocardiogram (ECG) were the most important features to predict both endpoints.

Abstract Coronary artery disease (CAD) often leads to adverse events resulting in significant disease burdens. Underlying risk factors often remain inapparent prior to disease incidence and the cardiovascular (CV) risk is not exclusively explained by traditional risk factors. Platelets inherently promote atheroprogression and enhanced platelet functions and distinct platelet lipid species are associated with disease severity in patients with CAD. Lipidomics data were acquired using mass spectrometry and processed alongside clinical data applying machine learning to model estimates of an increased CV risk in a consecutive CAD cohort (n = 595). By training machine learning models on CV risk measurements, stratification of CAD patients resulted in a phenotyping of risk groups. We found that distinct platelet lipids are associated with an increased CV or bleeding risk and independently predict adverse events. Notably, the addition of platelet lipids to conventional risk factors resulted in an increased diagnostic accuracy of patients with adverse CV events. Thus, patients with aberrant platelet lipid signatures and platelet functions are at elevated risk to develop adverse CV events. Machine learning combining platelet lipidome data and common clinical parameters demonstrated an increased diagnostic value in patients with CAD and might improve early risk discrimination and classification for CV events.

Abstract Background Diagnostic approaches like the nuclear magnetic resonance spectroscopy (NMR) based quantification of metabolites, lipoproteins, and inflammation markers has helped to identify typical alterations in the blood serum of COVID-19 patients. However, confounders such as sex, and comorbidities, which strongly influence the metabolome, were often not considered. Therefore, the aim of this NMR study was to consider sex, as well as arterial hypertension (AHT), when investigating COVID-19-positive serum samples in a large age-and sex matched cohort. Methods NMR serum data from 329 COVID-19 patients were compared with 305 healthy controls. 134 COVID-19 patients were affected by AHT. These were analyzed together with NMR data from 58 hypertensives without COVID-19. In addition to metabolite, lipoprotein, and glycoprotein data from NMR, common laboratory parameters were considered. Sex was considered in detail for all comparisons. Results Here, we show that several differences emerge from previous NMR COVID-19 studies when AHT is considered. Especially, the previously described triglyceride-rich lipoprotein profile is no longer observed in COVID-19 patients, nor an increase in ketone bodies. Further alterations are a decrease in glutamine, leucine, isoleucine, and lysine, citric acid, HDL-4 particles, and total cholesterol. Additionally, hypertensive COVID-19 patients show higher inflammatory NMR parameters than normotensive patients. Conclusions We present a more precise picture of COVID-19 blood serum parameters. Accordingly, considering sex and comorbidities should be included in future metabolomics studies for improved and refined patient stratification. Due to metabolic similarities with other viral infections, these results can be applied to other respiratory diseases in the future.

Abstract Spatial transcriptomics of histological sections have revolutionized research in life sciences and enabled unprecedented insights into genetic processes involved in tissue reorganization. However, in contrast to genomic analysis, the actual biomolecular composition of the sample has fallen behind, leaving a gap of potentially highly valuable information. Raman microspectroscopy provides untargeted spatiomolecular information at high resolution, capable of filling this gap. In this study we demonstrate spatially resolved Raman “spectromics” to reveal homogeneity, heterogeneity and dynamics of cell matrix on molecular levels by repurposing state-of-the-art bioinformatic analysis tools commonly used for transcriptomic analyses. By exploring sections of murine myocardial infarction and cardiac hypertrophy, we identify myocardial subclusters when spatially approaching the pathology, and define the surrounding metabolic and cellular (immune-) landscape. Our innovative, label-free, non-invasive “spectromics” approach could therefore open perspectives for a profound characterization of histological samples, while additionally allowing the combination with consecutive downstream analyses of the very same specimen.

Abstract Background MicroRNAs are paramount in post transcriptional gene regulation. We investigated platelet miRNAs in patients with CAD and examined potential associations with course of left ventricular ejection fraction (LVEF%). Materials and methods In a first cohort, 62 MiRNAs were measured in platelets of 100 patients suffering from CAD. Expression profiles of individuals with chronic coronary syndrome (CCS) and MI were compared (CCS n = 67, MI n = 33). Also, associations between miRNA profiles and change in left ventricular ejection fraction (LVEF%) were investigated. In a second cohort of patients suffering from CCS (n = 10), MI (n = 11) or no CAD (n = 13), we measured miRNA expression in platelets, platelet supernatant and serum. This was carried out before and after in vitro platelet activation with CRP. Results Platelet miRNAs 103a-3p and 155-5p demonstrated higher expression in patients with CCS then in individuals with MI. Furthermore, multiple miRNAs were significantly higher expressed in matched controls compared to MI patients. 8 miRNAs showed higher expression in patients with improving LVEF% after a 1-year follow-up. In our second cohort, we found higher concentrations of 6 miRNAs in the platelet supernatant of patients with CCS, MI and no CAD after in vitro platelet activation. Most of these miRNAs showed a higher abundance in serum of MI patients as compared to CCS. Conclusion Several miRNAs show higher expression in platelets of CCS compared to MI. After in vitro platelet activation, a release of multiple miRNAs out of the thrombocyte was observed. Furthermore, upregulation of serum miRNAs was found in MI patients when compared to CCS patients and individuals without CAD. Hence, platelets could present a source of upregulated circulating miRNAs in MI and additionally affect course of LVEF%.

We discuss a 38-year-old bodybuilder who had cardiogenic shock and multiorgan failure. The patient developed significant speech disorders resulting from thromboembolism of a huge, volatile left ventricular thrombus. Because of inoperability and the threat of severe ischemic stroke, the thrombus was removed with a snare and application of a cerebral embolic protection device. (Level of Difficulty: Advanced.)

Abstract Background Acute myocardial injury is associated with poor prognosis in respiratory tract infections. We aimed to highlight the differences in prevalence of myocardial injury and its impact on prognosis in patients with COVID-19 compared to those with seasonal influenza. Methods This was a single-center prospective cohort study with a historical control group. 300 age-/sex-matched SARS-CoV-2 and seasonal influenza positive patients were enrolled. Myocardial injury was assessed by electrocardiogram (ECG), transthoracic echocardiography and biomarkers including high-sensitivity troponin-I. All patients were followed-up for 30 days after enrollment for all-cause mortalitiy, admission to the intensive care unit (ICU) and mechanical ventilation. Results Right ventricular distress was more common in COVID-19 whereas pathological ECG findings and impaired left ventricular function were more prevalent among influenza patients. COVID-19 patients suffered from a higher percentage of hypertension and dyslipidaemia. Contrary to COVID-19, pericardial effusion at admission was associated with poor outcome in the influenza group. Severe course of disease and respiratory failure resulted in significantly higher rates of ICU treatment and mechanical ventilation in COVID-19 patients. Although distribution of myocardial injury was similar, significantly fewer cardiac catheterizations were performed in COVID-19 patients. However, number of cardiac catheterizations was low in both groups. Finally, 30-day mortality was significantly higher in COVID-19 compared to influenza patients. Conclusions In adults requiring hospitalization due to COVID-19 or seasonal influenza, cardiovascular risk factors and signs of myocardial distress differ significantly. Furthermore, cardiovascular comorbidities may impair prognosis in COVID-19 patients to a higher degree than in their influenza counterparts.

Background: Percutaneous mitral valve repair (PMVR) has evolved to be a standard procedure in suitable patients with mitral regurgitation (MR) not accessible for open surgery. Here, we analyzed the influence of the number and positioning of the clips implanted during the procedure on MR reduction analyzing also sub-collectives of functional and degenerative MR (DMR). Results: We included 410 patients with severe MR undergoing PMVR using the MitraClip® System. MR and reduction of MR were analyzed by TEE at the beginning and at the end of the PMVR procedure. To specify the clip localization, we sub-divided segment 2 into 3 sub-segments using the segmental classification of the mitral valve. Results: We found an enhanced reduction of MR predominantly in DMR patients who received more than one clip. Implantation of only one clip led to a higher MR reduction in patients with functional MR (FMR) in comparison to patients with DMR. No significant differences concerning pressure gradients could be observed in degenerative MR patients regardless of the number of clips implanted. A deterioration of half a grade of the achieved MR reduction was observed 6 months post-PMVR independent of the number of implanted clips with a better stability in FMR patients, who got 3 clips compared to patients with only one clip. Conclusions: In patients with FMR, after 6 months the reduction of MR was more stable with an increased number of implanted clips, which suggests that this specific patient collective may benefit from a higher number of clips.

ACKR3 is a critical regulator of platelet-mediated thrombosis and organ injury following ischemia/reperfusion. Platelet ACKR3 surface expression is independently associated with all-cause mortality in patients with cardiovascular diseases.