Artificial intelligence in cardiovascular prevention: new ways will open new doors.

Prevention and effective treatment of cardiovascular disease are progressive issues that grow in tandem with the average age of the world population. Over recent decades, the potential role of artificial intelligence in cardiovascular medicine has been increasingly recognized because of the incredible amount of real-world data (RWD) regarding patient health status and healthcare delivery that can be collated from a variety of sources wherein patient information is routinely collected, including patient registries, clinical case reports, reimbursement claims and billing reports, medical devices, and electronic health records. Like any other (health) data, RWD can be analysed in accordance with high-quality research methods, and its analysis can deliver valuable patient-centric insights complementing the information obtained from conventional clinical trials. Artificial intelligence application on RWD has the potential to detect a patient's health trajectory leading to personalized medicine and tailored treatment. This article reviews the benefits of artificial intelligence in cardiovascular prevention and management, focusing on diagnostic and therapeutic improvements without neglecting the limitations of this new scientific approach.

Cardiovascular implications of miRNAs in COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic continues to be a global challenge due to resulting morbidity and mortality. Cardiovascular (CV) involvement is a crucial complication in COVID-19, and no strategies are available to prevent or specifically address CV events in COVID patients. The identification of molecular partners contributing to CV manifestations in COVID-19 patients is crucial for providing early biomarkers, prognostic predictors and new therapeutic targets. The current report will focus on the role of miRNAs in CV complications associated with COVID-19. Indeed, miRNAs have been proposed as valuable biomarkers and predictors of both cardiac and vascular damage occurring in SARS-CoV-2 infection. Significance Statement It is essential to identify the molecular mediators of COVID-19 cardiovascular (CV) complications. This report focused on the role of miRNAs in CV complications associated with COVID-19, discussing their potential use as biomarkers, prognostic predictors, and therapeutic targets.

Acute Coronary Syndrome in Patients with SARS-CoV-2 Infection: Pathophysiology and Translational Perspectives

Acute coronary syndromes (ACS) may complicate the clinical course of patients with Coronavirus Disease 2019 (COVID-19). It is still unclear whether this condition is a direct consequence of the primary disease. However, several mechanisms including direct cellular damage, endothelial dysfunction, in-situ thrombosis, systemic inflammatory response, and oxygen supply-demand imbalance have been described in patients with COVID-19. The onset of a prothrombotic state may also be facilitated by the endothelial dysfunction secondary to the systemic inflammatory response and to the direct viral cell damage. Moreover, dysfunctional endothelial cells may enhance vasospasm and platelet aggregation. The combination of these factors promotes atherosclerotic plaque instability, thrombosis and, consequently, type 1 myocardial infarction. Furthermore, severe hypoxia due to extensive pulmonary involvement, in association with other conditions described in COVID-19 such as sepsis, tachyarrhythmias, anemia, hypotension, and shock, may lead to mismatch between oxygen supply and demand, and cause type 2 myocardial infarction. A deeper understanding of the potential pathophysiological mechanisms underlying ACS in patients with COVID-19 could help the therapeutic management of these very high-risk patients.

Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy).

COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.

Post-COVID-19 Syndrome: Involvement and Interactions between Respiratory, Cardiovascular and Nervous Systems.

Though the acute effects of SARS-CoV-2 infection have been extensively reported, the long-term effects are less well described. Specifically, while clinicians endure to battle COVID-19, we also need to develop broad strategies to manage post-COVID-19 symptoms and encourage those affected to seek suitable care. This review addresses the possible involvement of the lung, heart and brain in post-viral syndromes and describes suggested management of post-COVID-19 syndrome. Post-COVID-19 respiratory manifestations comprise coughing and shortness of breath. Furthermore, arrhythmias, palpitations, hypotension, increased heart rate, venous thromboembolic diseases, myocarditis and acute heart failure are usual cardiovascular events. Among neurological manifestations, headache, peripheral neuropathy symptoms, memory issues, lack of concentration and sleep disorders are most commonly observed with varying frequencies. Finally, mental health issues affecting mental abilities and mood fluctuations, namely anxiety and depression, are frequently seen. Finally, long COVID is a complex syndrome with protracted heterogeneous symptoms, and patients who experience post-COVID-19 sequelae require personalized treatment as well as ongoing support.

BPIFB4 Circulating Levels and Its Prognostic Relevance in COVID-19.

Aging and comorbidities make individuals at greatest risk of COVID-19 serious illness and mortality due to senescence-related events and deleterious inflammation. Long-living individuals (LLIs) are less susceptible to inflammation and develop more resiliency to COVID-19. As demonstrated, LLIs are characterized by high circulating levels of BPIFB4, a protein involved in homeostatic response to inflammatory stimuli. Also, LLIs show enrichment of homozygous genotype for the minor alleles of a 4 missense single-nucleotide polymorphism haplotype (longevity-associated variant [LAV]) in BPIFB4, able to counteract progression of diseases in animal models. Thus, the present study was designed to assess the presence and significance of BPIFB4 level in COVID-19 patients and the potential therapeutic use of LAV-BPIFB4 in fighting COVID-19. BPIFB4 plasma concentration was found significantly higher in LLIs compared to old healthy controls while it significantly decreased in 64 COVID-19 patients. Further, the drop in BPIFB4 values correlated with disease severity. Accordingly to the LAV-BPIFB4 immunomodulatory role, while lysates of SARS-CoV-2-infected cells induced an inflammatory response in healthy peripheral blood mononuclear cells in vitro, the co-treatment with recombinant protein (rh) LAV-BPIFB4 resulted in a protective and self-limiting reaction, culminating in the downregulation of CD69 activating-marker for T cells (both TCD4+ and TCD8+) and in MCP-1 reduction. On the contrary, rhLAV-BPIFB4 induced a rapid increase in IL-18 and IL-1b levels, shown largely protective during the early stages of the virus infection. This evidence, along with the ability of rhLAV-BPIFB4 to counteract the cytotoxicity induced by SARS-CoV-2 lysate in selected target cell lines, corroborates BPIFB4 prognostic value and open new therapeutic possibilities in more vulnerable people.

Timing of national lockdown and mortality in COVID-19: The Italian experience.

OBJECTIVE: To evaluate if the pandemic mitigation effects of lockdown in Italy have been influenced by the level of penetration of COVID-19 in Italian Regions at the onset of containment (March 9, 2020). METHODS: We collected data published day by daily from the first COVID-19 case until May 3, 2020, the end of lockdown, by Italy's Protezione Civile Department. Linear regression analyses were performed to evaluate possible correlations between the number of confirmed cases/100.000 residents and the number of new cases/100.000/day before lockdown, with the number of deaths/100.000 residents at sixty days, in each Italian region. RESULTS: We found a significant positive correlation between the number of confirmed cases before lockdown and mortality up to sixty days (p < 0.001; R2 = 0.57) as well as between the incidence rate of new cases per day and mortality up to sixty days (p < 0.001; R2 = 0.73). Regression coefficients indicated about two deaths up to sixty days for every new patient with confirmed COVID-19 before lockdown, and 37 deaths for every new infected subject per day until the lockdown decree of March 9, 2020. CONCLUSIONS: Every new infected subject before lockdown counted on the death toll of the COVID-19 pandemic in Italy.