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Background to date, more than 243 million COVID-19 cases have been diagnosed globally, with 4.94 million deaths, 489.000 new cases and 8.474 deaths per day. In Italy there are currently 4.73 million cases and 132.000 deaths. It is well known that the entry of the SARS- CoV-2 virus into cells is mediated by the binding between the virus Spike-glycoprotein (S) and the membrane ACE2-receptor (ACE2-R). When SARS-CoV-2 binds to ACE2-R, with subsequent membrane fusion and virus entry into the cell, a down-regulation of these receptors occurs. ACE2 –R downregulation plays a crucial role in the pulmonary and systemic inflammatory response. A serious clinical course appears to be associated with some factors such as age, previous pathologies and comorbidities. However, also a dysregulation of the RAA system linked to a different expression of ACE-2 R and TMPRSS2 gene polymorphisms and different serum levels of soluble ACE2 (sACE2), could be associated with abnormal inflammatory and immune response to SARS-CoV-2 infection. Aim of the Study we aimed to verify whether there is an association between the clinical course of COVID-19 patients (pts) and the presence of more frequent ACE2 and TMPRSS2 single-nucleotide polymorphisms (SNPs) and if sACE2 levels are related to specific ACE2 and TMPRSS2 polymorphic variants. Methods we consecutively enrolled subjects with previous documented SARS-CoV-2 infection and divided our sample into three groups: pts with asymptomatic course; pts with symptomatic course but without the need for hospitalization for COVID-19; pts with severe symptomatic course requiring hospitalization in intensive care unit. Data about age, clinical course, comorbidities, and therapies were collected. Blood samples were taken for the genetic analysis of the most frequent SNPs of the ACE2-R and TMPRSS2 detected in Italian population, in particular genotypic variants TT and CC of ACE2 SNPs 1 and 5 (rate of 5% and 14% respectively) and genotypic variants TT and CC of TMPRSS2 SNPs 2 and 3 (rate of 50% and 30% respective). Results among 178 pts enrolled up to March 2022, we have so far analyzed the genetic polymorphisms of 74 pts.; 21 (28%) were hospitalized for COVID-19, 38 (51%) had symptomatic course without hospitalization and 15 (21%) were completely pauci-asymptomatics. Serum concentrations of sACE2 and distribution of polymorphic variants in the three groups are summarized in Table 1. We found that sACE2 levels were higher in genotypic variant CC of SNP 1 of TMPRSS2 gene (Table 2). Considering that a high concentration of sACE2 outlines a proinflammatory condition, it could be hypothesized that the CC genotype may be a predisposing condition to the cytokine storm of COVID-19. Perspectives: Genetic analysis of ACE2 and TMPRSS2 SNPs will help to clarify the relationship between these polymorphic variant, sACE2 levels, risk of SARS-CoV2 infection and severity of clinical presentation of COVID-19 in patients with or without CV diseases.

Background It is well known that the entry of the SARS- CoV-2 virus into cells is mediated by the binding between the virus Spike-glycoprotein (S) and the membrane ACE2-receptor (ACE2R). When SARS-CoV-2 binds to ACE2R, with subsequent membrane fusion and virus entry into the cell, a down-regulation of these receptors occurs. ACE2R downregulation plays a crucial role in the pulmonary and systemic inflammatory response. Also ACE2 deficiency is thought to play an important role in the pathogenesis of SARS-CoV-2 infection. The down-regulation of ACE2 induced by viral infection could be particularly harmful in subjects with pre-existing ACE2 deficiency, for example due to advanced age, the presence of DM, arterial hypertension or pre-existing heart disease, including HF. Literature data suggest an association between the patient's age and comorbidities and a greater risk of severe clinical course and with a worse prognosis. However, serious clinical pictures requiring hospitalization or leading to death have also been observed in young subjects or subjects without comorbidities. Aim of the Study we aimed to identify predicting factors of a higher risk in terms of severity of the clinical course and worse prognosis in the population of the Brescia area, affected by a large number of cases in the first period of COVID-19 outbreak. In particular, we aimed to verify whether there is correlation between levels of serum ACE2 (sACE2) and the risk of SARS-CoV-2 infection, as well as between sACE2 and the different severity of the clinical manifestations of COVID-19 in patients with and without CV diseases. Methods we consecutively enrolled subjects with previous documented SARS-CoV-2 infection and divided our sample into three groups: pts with asymptomatic course; pts with symptomatic course but without the need for hospitalization for COVID-19; pts with severe symptomatic course requiring hospitalization in intensive care unit. Blood samples were taken for sACE2 dosage. We compared the concentrations of sACE2 in these groups in relation to the age, clinical course, comorbidities, and ongoing therapies. Results at March 2022, we enrolled 178 pts, 51 (28%) were hospitalized for COVID-19, whereas 78 (44%) had symptomatic course without hospitalization and 49 (28%) were completely pauci-asymptomatic. Only 6 pts (4%) had myocarditis or pericarditis SARS-CoV-2-related. Between hospitalized pts, male sex (67%), older age and higher BMI were most frequent. Moreover, chronic heart failure (20%), a diagnosis of cardiopathy (29%) and AF or atrial flutter (22%) were most frequent (Table 1). Plasma concentrations of sACE2 will be dosed and analyzed in relation to the clinical characteristics of each patient. Perspectives ACCEPT study will help to clarify the relationship between ACE2 molecule, the risk of SARS-CoV2 infection and the severity of clinical presentation of COVID-19 in pts with or without CV diseases.

Aims Estimation of left ventricle (LV) filling pressure is one of the most important parameters to provide information in clinical practice. However, the challenging in investigating this parameter through invasive methods makes it difficult to be used. The study aims to investigate the association between cardiac structure and function derived by transthoracic echocardiography (TTE) and left atrial (LA) invasive pressure (LAP). Methods The study was a multi-center prospective study enrolling 73 patients (mean age 65 ± 8, 27% female) undergoing primary catheter ablation for AF. Patients were evaluated and enrolled from June 2021 to April 2022. Complete TTE assessing measures of LV, LA and right ventricle (RV) structure and function including speckle tracking echocardiography, was performed at baseline. Echocardiographic data have been assessed the same day of the invasive measurement of the LAP during AF ablative procedure. Linear regression analysis has been performed to assess the relationship between measures of cardiac structure and function and LAP. Logistic regression analysis assessed the parameters associated with elevated LAP (≥ 15mmHg). Results Baseline clinical characteristics of the study population did not differ according to elevated LAP vs. non-elevated LAP. Patients with elevated LAP showed instead abnormal measures of LV global longitudinal strain, measures of LA structure and function, except for LA maximal volume, and RV structure and function. After multivariable adjustment, including demographic factors and comorbidities, E/e`(p = 0,024), LA minimal volume (p = 0,009), LA emptying fraction (LAEF) (p = 0,012), LA Reservoir (p = 0,039), TAPSE (p = 0,010) and RV free wall strain (p = 0,028), but not LA maximal volume (p = 0,11), were significantly associated with LAP. Similarly, these measures, but nor LA maximal volume, were significant determinants of elevated LAP. Overall, LA minimal volume and LAEF showed the best diagnostic accuracy to predict elevated LAP (AUC 0.72 and 0.73, respectively). Conclusions Novel measures of LA structure and function, but not standard assessment by LA maximal volume, were significantly associated with LAP in patients affected by AF. These measures, along with measures of LV and RV function may be used in the diagnostic assessment of filling pressure in ambulatory settings.

Aim Liver damage is frequently encountered in patients with cardiovascular (CV) disease, due to congestion or metabolic dysfunction-associated fatty liver disease (MAFLD). It has been shown that liver disease is associated with worse outcomes in patients with CV disease. Nevertheless, the association of liver disease with cardiac structure and function and CV events in patients with heart failure and reduced ejection fraction (HFrEF) is poorly known. Methods We retrospectively enrolled consecutive patients with HFrEF undergoing Cardiac Magnetic Resonance (CMR) Imaging. In addition to standard cardiac T1-mapping, 3 regions of interest were also defined at the liver parenchyma. Patients were stratified according to hepatic T1 mapping. Linear regression analysis adjusted for demographics and clinical characteristics was performed to cross-sectionally examine the association between hepatic T1-time on CMR and measures of cardiac structure and function. The Kaplan-Meier survival and Cox regression analyses were performed to prospectively investigate the association between hepatic T1-time and the composite adverse outcome of hospitalization for HF or all-cause death. Results Overall, 106 HFrEF patients were included in the study (mean age 56 ± 14 years, 75% male). Mean hepatic T1-time was 558 ± 70 ms. In logistic regression analysis, left-ventricle (LV) end-diastolic volume (EDV) (p = 0.027), left atrial volume (LAV) (p = 0.015), right-ventricle (RV) EDV (p < 0.001) and RVEF (p = 0.035) were positively associated with hepatic T1-time. Over a mean follow-up of 5 ± 2 years, 32 patients (30%) experienced the composite outcome at a rate of 6.7 per 100 person-year. In Cox regression analysis, higher hepatic T1-time was independently associated with an increased risk of developing the composite outcome (adjusted-hazard ratio 1.07, 95% confidence interval: 1.01–1.12, p = 0.011). In particular, patients with a hepatic T1-time ≥558 ms had a higher risk of adverse outcomes compared to those with a hepatic T1-time Conclusion Among HFrEF patients undergoing CMR, higher hepatic T1-time was significantly associated with poorer measures of cardiac size and function. Hepatic T1-time was also significantly associated with higher rates of hospitalization for HF or all-cause-mortality. This parameter may be useful to stratify HFrEF patients at risk of adverse cardiovascular outcomes.

Aims Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Prediction models are needed to optimize clinical management and to early stratify patients at a higher mortality risk. Machine learning (ML) algorithms represent a novel approach to identify a prediction model with a good discriminatory capacity to be easily used in clinical practice. Methods and results The Cardio-COVID is a multicentre observational study that involved a cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 [by real time reverse transcriptase—polymerase chain reaction (RT-PCR)] who were hospitalized in 13 Italian cardiology units from 1 March to 9 April 2020. Patients were followed-up after the COVID-19 diagnosis and all causes in-hospital mortality or discharge were ascertained until 23 April 2020. Variables with more than 20% of missing values were excluded. The Lasso procedure was used with a λ = 0.07 for reducing the covariates number. Mortality was estimated by means of a Random Forest (RF). The dataset was randomly divided in two subsamples with the same percentage of death/alive people of the entire sample: training set contained 80% of the data and test set the remaining 20%. The training set was used in the calibration procedure where a RF models in-hospital mortality with the covariates selected by Lasso. Its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity, and related 95% confidence interval (CI) computed with 10 000 stratified bootstrap replicates. From the RF the relative Variable Importance Measure (relVIM) was extracted to understand which of the selected variables had the greatest impact on outcome, providing a ranking from the most (relVIM = 100) to the less important variable. The model obtained was compared with the Gradient Boosting Machine (GBM) and with the logistic regression, where the predictions were cross validated. Finally, to understand if each model has the same performance in sample (training) and out of sample (test), the two AUCs were compared by means of the DeLong’s test. Among 701 patients enrolled (mean age 67.2 ± 13.2 years, 69.5% males), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9–24) days. Variables selected by the Lasso were: age, Oxygen saturation, PaO2/FiO2, Creatinine Clearance and elevated Troponin. Compared with those who survived, deceased patients were older, had a lower blood oxygenation, a lower creatinine clearance levels and higher prevalence of elevated Troponin (all P Conclusions In a large COVID-19 population, we showed that a customizable ML-based score derived from clinical variables, is feasible and effective for the prediction of in-hospital mortality.

Aims The SARS-CoV-2 infection is mostly characterized by acute lung injury. Yet, some COVID-19 patients showed also neurological signs, acute myocardial injury, heart failure, myocarditis, and hypercoagulability, such as pulmonary embolism. Cardiac biomarkers can play an essential role in the diagnosis, management, and prognosis of COVID-19. In fact, during hospitalization, these patients develop biochemical abnormalities, with increasing of all Troponins (TnT), B-type natriuretic peptide (NT-pro-BNP) and creatine kinase-myocardial band (CK-MB) levels. This situation helps us to predict adverse outcomes, especially in patients with cardiovascular comorbidities or risk factors. Data emerged demonstrated a myocardial involvement which determines a high risk of adverse events and increasing of mortality. Methods and results Lots of meta-analysis emphasize that a great number of hospitalized patients with moderate and severe forms of COVID-19 developed acute myocardial damage, defined as an increase of cardiac biomarkers, such NT-pro-BNP, CK-MB, and of all type of troponins. The highest mortality rate is related with progressively increasing biomarkers levels and with a history of cardiovascular disease. In fact, the biomarkers dosage should be considered as a prognostic marker in all patients with COVID-19 disease at admission, during hospitalization and in the case of clinical deterioration. Our purpose is to evaluate cardiovascular prognostic factors in COVID-19 disease throughout the analysis of cardiac biomarkers to early identify the most serious patients and to optimize their outcomes. Results of aforementioned studies underline how cardiac biomarkers are associated with severe form of COVID-19 infection. Above all, higher levels of these biomarkers are significantly associated with an increased risk of the mortality in COVID-19 infected patients. Therefore, has been demonstrated COVID-19 infection is more severe in those patients with a previous history of arterial hypertension, cardiovascular diseases. In addition to classical laboratory parameters evaluated in COVID-19 infection, such as C Reactive Protein (CRP), d-dimer, and lactate dehydrogenase (LDH), which are currently used in clinical practice, others biomarkers could potentially be useful for screening, clinical management, and prevention of serious complications. Therefore, it is clinically significant that fluctuating levels of myocardial biomarkers are closely monitored and patients with high levels of myocardial biomarkers are treated promptly to improve prognosis. At the end, on basis of symptoms and cardiac biomarkers patients could be divided in mild, severe and critical. Conclusions Biomarkers of acute myocardial injury play an important role in predicting worsening prognosis for COVID-19 patients with and without myocardial injury. They are not only predictive of disease severity, but are also helpful for therapeutic management, based on drugs preventing the activation of coagulation processes. It’s important, above all, to identify a laboratory score, made by haematological, inflammatory, biochemical, and immunological parameters, may help to stratify COVID-19 positive patients into risk categories for deciding therapeutic management, thus avoiding cardiac compromise which, as we have previously analysed, is an indication of a poor prognosis.