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Aims: To assess the association between combination, dose and use of current guideline‐recommended target doses (TD) of renin–angiotensin system inhibitors (RASi), angiotensin receptor–neprilysin inhibitors (ARNi) and β‐blockers, and outcomes in a large and unselected contemporary cohort of patients with heart failure (HF) and reduced ejection fraction. Methods and results: Overall, 17 809 outpatients registered in the Swedish Heart Failure Registry (SwedeHF) from May 2000 to December 2018, with ejection fraction <40% and duration of HF ≥90 days were selected. Primary outcome was a composite of time to cardiovascular death and first HF hospitalization. Compared with no use of RASi or ARNi, the adjusted hazard ratio (HR) (95% confidence interval [CI]) was 0.83 (0.76–0.91) with <50% of TD, 0.78 (0.71–0.86) with 50%–99%, and 0.73 (0.67–0.80) with ≥100% of TD. Compared with no use of β‐blockers, the adjusted HR (95% CI) was 0.86 (0.76–0.91), 0.81 (0.74–0.89) and 0.74 (0.68–0.82) with <50%, 50%–99% and ≥100% of TD, respectively. Patients receiving both an angiotensin‐converting enzyme inhibitor (ACEi)/angiotensin receptor blocker (ARB)/ARNi and a β‐blocker at 50%–99% of TD had a lower adjusted risk of the primary outcome compared with patients only receiving one drug, i.e. ACEi/ARB/ARNi or β‐blocker, even if this was at ≥100% of TD. Conclusion: Heart failure with reduced ejection fraction patients using higher doses of RASi or ARNi and β‐blockers had lower risk of cardiovascular death or HF hospitalization. Use of two drug classes at 50%–99% of TD dose was associated with lower risk than one drug class at 100% of TD. [ABSTRACT FROM AUTHOR]

One in 10 persons in the world aged 40 years and older will develop the syndrome of HFpEF (heart failure with preserved ejection fraction), the most common form of chronic cardiovascular disease for which no effective therapies are currently available. Metabolic disturbance and inflammatory burden contribute importantly to HFpEF pathogenesis. The interplay within these two biological processes is complex; indeed, it is now becoming clear that the notion of metabolic inflammation—metainflammation—must be considered central to HFpEF pathophysiology. Inflammation and metabolism interact over the course of syndrome progression, and likely impact HFpEF treatment and prevention. Here, we discuss evidence in support of a causal, mechanistic role of metainflammation in shaping HFpEF, proposing a framework in which metabolic comorbidities profoundly impact cardiac metabolism and inflammatory pathways in the syndrome. [ABSTRACT FROM AUTHOR]

Background: Heart failure (HF) is a multifaceted clinical syndrome characterized by different etiologies, risk factors, comorbidities, and a heterogeneous clinical course. The current model, based on data from clinical trials, is limited by the biases related to a highly-selected sample in a protected environment, constraining the applicability of evidence in the real-world scenario. If properly leveraged, the enormous amount of data from real-world may have a groundbreaking impact on clinical care pathways. We present, here, the development of an HF DataMart framework for the management of clinical and research processes., Methods: Within our institution, Fondazione Policlinico Universitario A. Gemelli in Rome (Italy), a digital platform dedicated to HF patients has been envisioned (GENERATOR HF DataMart), based on two building blocks: 1. All retrospective information has been integrated into a multimodal, longitudinal data repository, providing in one single place the description of individual patients with drill-down functionalities in multiple dimensions. This functionality might allow investigators to dynamically filter subsets of patient populations characterized by demographic characteristics, biomarkers, comorbidities, and clinical events (e.g., re-hospitalization), enabling agile analyses of the outcomes by subsets of patients. 2. With respect to expected long-term health status and response to treatments, the use of the disease trajectory toolset and predictive models for the evolution of HF has been implemented. The methodological scaffolding has been constructed in respect of a set of the preferred standards recommended by the CODE-EHR framework., Results: Several examples of GENERATOR HF DataMart utilization are presented as follows: to select a specific retrospective cohort of HF patients within a particular period, along with their clinical and laboratory data, to explore multiple associations between clinical and laboratory data, as well as to identify a potential cohort for enrollment in future studies; to create a multi-parametric predictive models of early re-hospitalization after discharge; to cluster patients according to their ejection fraction (EF) variation, investigating its potential impact on hospital admissions., Conclusion: The GENERATOR HF DataMart has been developed to exploit a large amount of data from patients with HF from our institution and generate evidence from real-world data. The two components of the HF platform might provide the infrastructural basis for a combined patient support program dedicated to continuous monitoring and remote care, assisting patients, caregivers, and healthcare professionals., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 D'Amario, Laborante, Delvinoti, Lenkowicz, Iacomini, Masciocchi, Luraschi, Damiani, Rodolico, Restivo, Ciliberti, Paglianiti, Canonico, Paternello, Cesario, Valentini, Scambia and Crea.)

Heart failure (HF) is marked by distinctive changes in myocardial uptake and utilization of energy substrates. Among the different types of HF, HF with preserved ejection fraction (HFpEF) is a highly prevalent, complex, and heterogeneous condition for which metabolic derangements seem to dictate disease progression. Changes in intermediate metabolism in cardiometabolic HFpEF-among the most prevalent forms of HFpEF-have a large impact both on energy provision and on a number of signalling pathways in the heart. This dual, metabolic vs. signalling, role is played in particular by long-chain fatty acids (LCFAs) and short-chain carbon sources [namely, short-chain fatty acids (SCFAs) and ketone bodies (KBs)]. LCFAs are key fuels for the heart, but their excess can be harmful, as in the case of toxic accumulation of lipid by-products (i.e. lipotoxicity). SCFAs and KBs have been proposed as a potential major, alternative source of energy in HFpEF. At the same time, both LCFAs and short-chain carbon sources are substrate for protein post-translational modifications and other forms of direct and indirect signalling of pivotal importance in HFpEF pathogenesis. An in-depth molecular understanding of the biological functions of energy substrates and their signalling role will be instrumental in the development of novel therapeutic approaches to HFpEF. Here, we summarize the current evidence on changes in energy metabolism in HFpEF, discuss the signalling role of intermediate metabolites through, at least in part, their fate as substrates for post-translational modifications, and highlight clinical and translational challenges around metabolic therapy in HFpEF., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Aims: Adenosine has been tested in several randomized controlled trials (RCTs) to minimize the incidence of coronary microvascular obstruction (CMVO). The aim of this study was to pool all the RCTs comparing intracoronary or intravenous adenosine versus placebo in patients with acute coronary syndrome (ACS) undergoing myocardial revascularization., Methods and Results: PubMed and Scopus electronic databases were scanned for eligible studies up to 5th June 2022. A total of 26 RCTs with 5843 patients were included. Efficacy endpoints were major adverse cardiac events (MACE), all-cause death, non-fatal myocardial infarction, and heart failure. Atrioventricular blocks and ventricular fibrillation/sustained ventricular tachycardia (VF/SVT) were the safety endpoints. Myocardial blush grade, thrombolysis in myocardial infarction (TIMI) flow grade, left ventricular ejection fraction (LVEF), infarct size, and ST-segment resolution were also assessed. Adenosine administration was not associated with any clinical benefit in terms of MACE, all-cause death, non-fatal myocardial infarction, and heart failure. However, adenosine was associated with an increased rate of advanced atrioventricular blocks and of VF/SVT in studies with total mean ischaemic time >3 h, compared to placebo. Remarkably, among patients undergoing percutaneous coronary intervention, adenosine was associated with reduced myocardial blush grade 0-1 and TIMI flow grade 0-2, compared to placebo. Furthermore, adenosine did not show favourable effects on LVEF and infarct size., Conclusion: Adenosine infusion, as adjunctive therapy in ACS, was associated with an increased risk of advanced atrioventricular blocks and increased rates of adenosine-triggered ventricular arrhythmias in patients with long ischaemic time, without providing any clinical benefit compared to placebo., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

New technologies have been recently introduced to improve the monitoring of patients with chronic syndromes such as heart failure. Devices can now be employed to gather large amounts of data and data processing through artificial intelligence techniques may improve heart failure management and reduce costs. The analysis of large datasets using an artificial intelligence technique is leading to a paradigm shift in the era of precision medicine. However, the assessment of clinical safety and the evaluation of the potential benefits is still a matter of debate. In this article, the authors aim to focus on the development of these new tools and to draw the attention to their transition in daily clinical practice., Competing Interests: Disclosure: The authors have no conflicts of interest to declare., (Copyright © 2020, Radcliffe Cardiology.)