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Aims The Heart Failure Association of the European Society of Cardiology (HFA-ESC) proposed a definition of advanced heart failure (HF) that has not been validated, yet. We assessed its prognostic impact in a consecutive series of patients with high-risk HF. Methods and results The HELP-HF registry enrolled consecutive patients with HF and at least one high-risk 'I NEED HELP' marker, evaluated at four Italian centres between 1(st) January 2020 and 30(th) November 2021. Patients meeting the HFA-ESC advanced HF definition were compared to patients not meeting this definition. The primary endpoint was the composite of all-cause mortality or first HF hospitalization. Out of 4753 patients with HF screened, 1149 (24.3%) patients with at least one high-risk 'I NEED HELP' marker were included (mean age 75.1 +/- 11.5 years, 67.3% male, median left ventricular ejection fraction [LVEF] 35% [interquartile range 25%-50%]). Among them, 193 (16.8%) patients met the HFA-ESC advanced HF definition. As compared to others, these patients were younger, had lower LVEF, higher natriuretic peptides and a worse clinical profile. The 1-year rate of the primary endpoint was 69.3% in patients with advanced HF according to the HFA-ESC definition versus 41.8% in the others (hazard ratio [HR] 2.23, 95% confidence interval [CI] 1.82-2.74, p < 0.001). The prognostic impact of the HFA-ESC advanced HF definition was confirmed after multivariable adjustment for relevant covariates (adjusted HR 1.98, 95% CI 1.57-2.50, p < 0.001). Conclusions The HFA-ESC advanced HF definition had a strong prognostic impact in a contemporary, real-world, multicentre high-risk cohort of patients with HF.

Aims To evaluate the prognostic impact of pre-procedural right ventricular longitudinal strain (RVLS) in patients with secondary mitral regurgitation (SMR) undergoing transcatheter edge-to-edge repair (TEER) in comparison with conventional echocardiographic parameters of RV function. Methods and results This is a retrospective study including 142 patients with SMR undergoing TEER at two Italian centres. At 1-year follow-up 45 patients reached the composite endpoint of all-cause death or heart failure hospitalization. The best cut-off value of RV free-wall longitudinal strain (RVFWLS) to predict outcome was −18% [sensitivity 72%, specificity of 71%, area under curve (AUC) 0.78, P < 0.001], whereas the best cut-off value of RV global longitudinal strain (RVGLS) was −15% (sensitivity 56%, specificity 76%, AUC 0.69, P < 0.001). Prognostic performance was suboptimal for tricuspid annular plane systolic excursion, Doppler tissue imaging-derived tricuspid lateral annular systolic velocity and fractional area change (FAC). Cumulative survival free from events was lower in patients with RVFWLS ≥ −18% vs. RVFWLS < −18% (44.0% vs. 85.4%; < 0.001) as well as in patients with RVGLS ≥ −15% vs. RVGLS < −15% (54.9% vs. 81.7%; P < 0.001). At multivariable analysis FAC, RVGLS and RVFWLS were independent predictors of events. The identified cut-off of RVFWLS and RVGLS both resulted independently associated with outcomes. Conclusion RVLS is a useful and reliable tool to identify patients with SMR undergoing TEER at high risk of mortality and HF hospitalization, on top of other clinical and echocardiographic parameters, with RVFWLS offering the best prognostic performance.

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.

Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission.We studied an Italian cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 who were hospitalized in 13 cardiology units during Spring 2020. The Lasso procedure was used to select the most relevant covariates. The dataset was randomly divided into a training set containing 80% of the data, used for estimating the model, and a test set with the remaining 20%. A Random Forest modeled in-hospital mortality with the selected set of covariates: its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity and related 95% confidence interval (CI). This model was then compared with the one obtained by the Gradient Boosting Machine (GBM) and with logistic regression. Finally, to understand if each model has the same performance in the training and test set, the two AUCs were compared using the DeLong's test. Among 701 patients enrolled (mean age 67.2 ± 13.2 years, 69.5% male individuals), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9-24) days. Variables selected by the Lasso procedure 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, lower creatinine clearance levels and higher prevalence of elevated troponin (all P 0.001). The best performance out of the samples was provided by Random Forest with an AUC of 0.78 (95% CI: 0.68-0.88) and a sensitivity of 0.88 (95% CI: 0.58-1.00). Moreover, Random Forest was the unique model that provided similar performance in sample and out of sample (DeLong test P = 0.78).In a large COVID-19 population, we showed that a customizable machine learning-based score derived from clinical variables is feasible and effective for the prediction of in-hospital mortality.

Background: Preprocedural right ventricular–to–pulmonary artery (RV-PA) coupling is a major predictor of outcome in patients with secondary mitral regurgitation (SMR) undergoing transcatheter edge-to-edge mitral valve repair (M-TEER). However, clinical significance of changes in RV-PA coupling after M-TEER is unknown. Objectives: The aim of this study was to evaluate changes in RV-PA coupling after M-TEER, their prognostic value, and predictors of improvement. Methods: This was a retrospective observational study, including patients undergoing successful M-TEER (residual mitral regurgitation ≤2+ at discharge) for SMR at 13 European centers and with complete echocardiographic data at baseline and short-term follow-up (30-180 days). RV-PA coupling was assessed with the use of echocardiography as the ratio of tricuspid annular plane systolic excursion to pulmonary artery systolic pressure (TAPSE/PASP). All-cause death was assessed at the longest available follow-up starting from the time of the echocardiographic reassessment. Results: Among 501 patients included, 331 (66%) improved their TAPSE/PASP after M-TEER (responders) at short-term follow-up (median: 89 days; IQR: 43-159 days), whereas 170 (34%) did not (nonresponders). Lack of previous cardiac surgery, low postprocedural mitral mean gradient, low baseline TAPSE, high baseline PASP, and baseline tricuspid regurgitation were independently associated with TAPSE/PASP improvement after M-TEER. Compared with nonresponders, responders had lower New York Heart Association functional class and less heart failure hospitalizations at short-term follow-up. Improvement in TAPSE/PASP was independently associated with reduced risk of mortality at long-term follow-up (584 days; IQR: 191-1,243 days) (HR: 0.65 [95% CI: 0.42-0.92]; P = 0.017). Conclusions: In patients with SMR, improvement in TAPSE/PASP after successful M-TEER is predicted by baseline clinical and echocardiographic variables and postprocedural mitral gradient, and is associated with a better outcome.

INTRODUCTION: The role of sex compared to comorbidities and other prognostic variables in patients with coronavirus disease (COVID-19) is unclear. METHODS: This is a retrospective observational study on patients with COVID-19 infection, referred to 13 cardiology units. The primary objective was to assess the difference in risk of death between the sexes. The secondary objective was to explore sex-based heterogeneity in the association between demographic, clinical and laboratory variables, and patients' risk of death. RESULTS: Seven hundred and one patients were included: 214 (30.5%) women and 487 (69.5%) men. During a median follow-up of 15 days, deaths occurred in 39 (18.2%) women and 126 (25.9%) men. In a multivariable Cox regression model, men had a nonsignificantly higher risk of death vs. women (P = 0.07).The risk of death was more than double in men with a low lymphocytes count as compared with men with a high lymphocytes count [overall survival hazard ratio (OS-HR) 2.56, 95% confidence interval (CI) 1.72-3.81]. In contrast, lymphocytes count was not related to death in women (P = 0.03).Platelets count was associated with better outcome in men (OS-HR for increase of 50 × 103 units: 0.88 95% CI 0.78-1.00) but not in women. The strength of association between higher PaO2/FiO2 ratio and lower risk of death was larger in women (OS-HR for increase of 50 mmHg/%: 0.72, 95% CI 0.59-0.89) vs. men (OS-HR: 0.88, 95% CI 0.80-0.98; P = 0.05). CONCLUSIONS: Patients' sex is a relevant variable that should be taken into account when evaluating risk of death from COVID-19. There is a sex-based heterogeneity in the association between baseline variables and patients' risk of death.

Data concerning the combined prognostic role of natriuretic peptide (NP) and troponin in patients with COVID-19 are lacking. The aim of the study is to evaluate the combined prognostic value of NPs and troponin in hospitalized COVID-19 patients. From March 1, 2020 to April 9, 2020, consecutive patients with COVID-19 and available data on cardiac biomarkers at admission were recruited. Patients admitted for acute coronary syndrome were excluded. Troponin levels were defined as elevated when greater than the 99th percentile of normal values. NPs were considered elevated if above the limit for ruling in acute heart failure (HF). A total of 341 patients were included in this study, mean age 68 +/-& nbsp;13 years, 72% were men. During a median follow-up period of 14 days, 81 patients (24%) died. In the Cox regression analysis, patients with elevated both NPs and troponin levels had higher risk of death compared with those with normal levels of both (hazard ratio 2.94; 95% confidence interval 1.31 to 6.64; p = 0.009), and this remained significant after adjustment for age, gender, oxygen saturation, HF history, and chronic kidney disease. Interestingly, NPs provided risk stratification also in patients with normal troponin values (hazard ratio 2.86; 95% confidence interval 1.21 to 6.72; p = 0.016 with high NPs levels). These data show the combined prognostic role of troponin and NPs in COVID-19 patients. NPs value may be helpful in identifying patients with a worse prognosis among those with normal troponin values. Further, NPs' cut-point used for diagnosis of acute HF has a predictive role in patients with COVID-19.

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.

Heart failure (HF) is characterized by frequent hospital admissions due to acute decompensation and shortened life span with a progressive clinical course leading to an advanced stage where traditional therapies become ineffective. Due to aging of the population and improved therapies, only a small of proportion of patients with advanced HF are candidates for surgical treatments, such as mechanical circulatory support or heart transplantation. In most cases, prompt identification and management of congestion is paramount to improving symptoms and quality of life and avoiding progression to severe multiorgan dysfunction and death.