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The aim of this study was to evaluate the effects of Sacubitril/Valsartan (S/V) on clinical, laboratory and echocardiographic parameters and outcomes in a real-world population with heart failure with reduced ejection fraction (HFrEF). This was a prospective observational study enrolling patients with HFrEF undergoing treatment with S/V. The primary outcome was the composite of cardiac death and HF rehospitalization at 12 months follow-up; secondary outcomes were all-cause death, cardiac death and the occurrence of rehospitalization for worsening HF. The clinical outcome was compared with a retrospective cohort of 90 HFrEF patients treated with standard medical therapy. The study included 90 patients (66.1 ± 11.7 years) treated with S/V. The adjusted regression analysis showed a significantly lower risk for the primary outcome (HR:0.31; 95%CI, 0.11–0.83; p = 0.019) and for HF rehospitalization (HR:0.27; 95%CI, 0.08–0.94; p = 0.039) in S/V patients as compared to the control group. A significant improvement in NYHA class, left ventricular ejection fraction, left ventricular end systolic volume and systolic pulmonary arterial pressure was observed up to 6 months. S/V did not affect negatively renal function and was associated with a significantly lower dose of furosemide dose prescribed at 6- and 12-month follow-up. In this study, S/V reduced the risk of HF rehospitalization and cardiac death at 1 year in patients with HFrEF. S/V improved NYHA class, echocardiographic parameters and need of furosemide, and preserved renal function.

Aging can be seen as process characterized by accumulation of oxidative stress induced damage. Oxidative stress derives from different endogenous and exogenous processes, all of which ultimately lead to progressive loss in tissue and organ structure and functions. The oxidative stress theory of aging expresses itself in age-related diseases. Aging is in fact a primary risk factor for many diseases and in particular for cardiovascular diseases and its derived morbidity and mortality. Here we highlight the role of oxidative stress in age-related cardiovascular aging and diseases. We take into consideration the molecular mechanisms, the structural and functional alterations, and the diseases accompanied to the cardiovascular aging process.

Background A high prevalence of cardiovascular risk factors including age, male sex, hypertension, diabetes, and tobacco use, has been reported in patients with Coronavirus disease 2019 (COVID-19) who experienced adverse outcome. The aim of this study was to investigate the relationship between cardiovascular risk factors and in-hospital mortality in patients with COVID-19. Methods MEDLINE, Cochrane, Web of Sciences, and SCOPUS were searched for retrospective or prospective observational studies reporting data on cardiovascular risk factors and in-hospital mortality in patients with COVID-19. Univariable and multivariable age-adjusted analyses were conducted to evaluate the association between cardiovascular risk factors and the occurrence of in-hospital death. Results The analysis included 45 studies enrolling 18,300 patients. The pooled estimate of in-hospital mortality was 12% (95% CI 9–15%). The univariable meta-regression analysis showed a significant association between age (coefficient: 1.06; 95% CI 1.04–1.09; p < 0.001), diabetes (coefficient: 1.04; 95% CI 1.02–1.07; p < 0.001) and hypertension (coefficient: 1.01; 95% CI 1.01–1.03; p = 0.013) with in-hospital death. Male sex and smoking did not significantly affect mortality. At multivariable age-adjusted meta-regression analysis, diabetes was significantly associated with in-hospital mortality (coefficient: 1.02; 95% CI 1.01–1.05; p = 0.043); conversely, hypertension was no longer significant after adjustment for age (coefficient: 1.00; 95% CI 0.99–1.01; p = 0.820). A significant association between age and in-hospital mortality was confirmed in all multivariable models. Conclusions This meta-analysis suggests that older age and diabetes are associated with higher risk of in-hospital mortality in patients infected by SARS-CoV-2. Conversely, male sex, hypertension, and smoking did not independently correlate with fatal outcome.

Cardiovascular disease (CVD) accounts for the majority of death and hospitalization, health care expenditures and loss of productivity in developed country. CVD research, thus, plays a key role for improving patients' outcomes as well as for the sustainability of health systems. The increasing costs and complexity of modern medicine along with the fragmentation in healthcare organizations interfere with improving quality care and represent a missed opportunity for research. The advancement in diagnosis, therapy and prognostic evaluation of patients with CVD, indeed, is frustrated by limited data access to selected small patient populations, not standardized nor computable definition of disease and lack of approved relevant patient-centered outcomes. These critical issues results in a deep mismatch between randomized controlled trials and real-world setting, heterogeneity in treatment response and wide inter-individual variation in prognosis. Big data approach combines millions of people's electronic health records (EHR) from different resources and provides a new methodology expanding data collection in three direction: high volume, wide variety and extreme acquisition speed. Large population studies based on EHR holds much promise due to low costs, diminished study participant burden, and reduced selection bias, thus offering an alternative to traditional ascertainment through biomedical screening and tracing processes. By merging and harmonizing large data sets, the researchers aspire to build algorithms that allow targeted and personalized CVD treatments. In current paper, we provide a critical review of big health data for cardiovascular research, focusing on the opportunities of this largely free data analytics and the challenges in its realization.

Long-COVID-19 refers to the signs and symptoms that continue or develop after the “acute COVID-19” phase. These patients have an increased risk of multiorgan dysfunction, readmission, and mortality. In Long-COVID-19 patients, it is possible to detect a persistent increase in D-Dimer, NT-ProBNP, and autonomic nervous system dysfunction. To verify the dysautonomia hypothesis in Long-COVID-19 patients, we studied heart rate variability using 12-lead 24-h ECG monitoring in 30 Long-COVID-19 patients and 20 No-COVID patients. Power spectral analysis of heart rate variability was lower in Long-COVID-19 patients both for total power (7.46 ± 0.5 vs. 8.08 ± 0.6; p < 0.0001; Cohens-d = 1.12) and for the VLF (6.84 ± 0.8 vs. 7.66 ± 0.6; p < 0.0001; Cohens-d = 1.16) and HF (4.65 ± 0.9 vs. 5.33 ± 0.9; p = 0.015; Cohens-d = 0.76) components. The LF/HF ratio was significantly higher in Long-COVID-19 patients (1.46 ± 0.27 vs. 1.23 ± 0.13; p = 0.001; Cohens-d = 1.09). On multivariable analysis, Long-COVID-19 is significantly correlated with D-dimer (standardized β-coefficient = 0.259), NT-ProBNP (standardized β-coefficient = 0.281), HF component of spectral analysis (standardized β-coefficient = 0.696), and LF/HF ratio (standardized β-coefficient = 0.820). Dysautonomia may explain the persistent symptoms in Long COVID-19 patients. The persistence of a procoagulative state and an elevated myocardial strain could explain vagal impairment in these patients. In Long-COVID-19 patients, impaired vagal activity, persistent increases of NT-ProBNP, and a prothrombotic state require careful monitoring and appropriate intervention.

Vitamin D is rightly recognized as an essential key factor in the regulation of calcium and phosphate homeostasis, affecting primary adequate bone mineralization. In the last decades, a more complex and wider role of vitamin D has been postulated and demonstrated. Cardiovascular diseases have been found to be strongly related to vitamin D levels, especially to its deficiency. Pre-clinical studies have suggested a direct role of vitamin D in the regulation of several pathophysiological pathways, such as endothelial dysfunction and platelet aggregation; moreover, observational data have confirmed the relationship with different conditions, including coronary artery disease, heart failure, and hypertension. Despite the significant evidence available so far, most clinical trials have failed to prove any positive impact of vitamin D supplements on cardiovascular outcomes. This discrepancy indicates the need for further information and knowledge about vitamin D metabolism and its effect on the cardiovascular system, in order to identify those patients who would benefit from vitamin D supplementation.

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the “black-box” nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients’ risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

To evaluate the prognostic impact of diabetes mellitus (DM) in patients with Infective Endocarditis (IE). 375 patients with diagnosis of IE referred to our Hospital between 1994-2017 were retrospectively included; diabetes was reported in 129 (34.4%). Diabetic patients were older than non-diabetic (66±1 vs. 57±2 years, p<0.001) and showed a higher prevalence of comorbidities such as hypertension (75 vs. 54%, p<0.001), coronary artery disease (30 vs. 12%, p<0.001) and history of heart failure (HF; 24 vs. 13%, p = 0.021). Echocardiography showed a higher incidence of paravalvular complications (82 vs. 64%, p<0.001) and a lower left ventricular ejection fraction (LVEF; 52±11 vs. 55±10%, p = 0.001) in diabetic than in non-diabetic patients. In-hospital mortality was higher in diabetic patients (83 vs. 74%; p = 0.030). At logistic regression, history of HF (OR = 3.1, 95%CI: 1.87-5.29, p<0.001) resulted an independent predictor of in-hospital death. At long-term follow-up [median 24(7-84) months], the Kaplan-Meier analysis showed a significantly lower survival free from all-cause death in the group with diabetes (Log-rank<0.001). At the propensity score adjusted Cox multivariable analysis, DM (HR = 1.76, 95%CI: 1.18-2.6, p = 0.005), age (HR = 1.03, 95%CI: 1.02-1.05, p<0.001), intravenous drug users (HR = 5.42, 95%CI: 2.55-11.51, p<0.001) and low LVEF (HR = 0.98, 95%CI: 0.96-0.99, p = 0.013) were independently associated to a higher mortality. In patients with IE, DM is associated to a higher prevalence of anatomic complications and a more impaired LVEF. Diabetic patients show a significantly lower survival both in hospital and during follow-up compared to the non-diabetic ones.

Recent scientific literature has investigated the cardiovascular implications of COVID-19. The mechanisms of cardiovascular damage seem to involve the protein angiotensin-converting enzyme 2 (ACE2), to which severe acute respiratory syndrome (SARS) coronavirus-2 (CoV-2) binds to penetrate cells and other mechanisms, most of which are still under study. Cardiovascular sequelae of COVID-19 include heart failure, cardiomyopathy, acute coronary syndrome, arrhythmias, and venous thromboembolism. This article aims to collect scientific evidence by exploiting PubMed, Scopus, and Pedro databases to highlight the cardiovascular complications of COVID-19 and to define the physiotherapy treatment recommended for these patients. Exercise training (ET), an important part of cardiac rehabilitation, is a powerful tool in physiotherapy, capable of inducing significant changes in the cardiovascular system and functional in the recovery of endothelial dysfunction and for the containment of thromboembolic complications. In conclusion, due to the wide variety of possible exercise programs that can be obtained by combining intensity, duration, and speed in various ways, and by adjusting the program based on continuous patient monitoring, exercise training is well suited to the treatment of post-COVID patients with an impaired cardiovascular system of various degrees.

The purpose of the current study was to compare the efficacy and safety of edoxaban versus vitamin K antagonist (VKA) therapy among a cohort of elderly patients (ie, those aged ≥75 years) with atrial fibrillation (AF) in a real-life setting. A propensity score–matched cohort observational study was performed comparing the safety and efficacy of edoxaban versus VKA therapy among a cohort of elderly (aged ≥75 years) patients with AF in a real-life setting. Follow-up data were obtained through outpatient visits at 1, 3, and every 6 months. The primary safety outcome was major bleeding. The primary efficacy outcome was the composite of stroke, transient ischemic attack, and systemic embolism. A total of 130 patients receiving edoxaban 60 mg (EDO) treatment were compared with the same number of VKA recipients. The mean follow-up was 16 (2.6) months. The cumulative incidence of thromboembolic events in the EDO and VKA groups was 1.5% (2 of 130) and 2.3% (3 of 130), respectively (P < 0.6). The cumulative incidence of major bleeding events was 1.5% (2 of 130) in the EDO group and 3.1% (4 of 130) in the VKA group (P < 0.4). The total anticoagulant therapy discontinuation rate was 2.3% (3 of 130) in the EDO group and 4.6% (6 of 130) in the VKA group (P < 0.3). A nonsignificant trend in improved adherence was observed between the EDO and VKA groups (81% vs 78%; P = 0.6). Edoxaban therapy showed a good real-life performance among elderly patients (aged ≥75 years) with AF.