Search

In recent times, there have been notable changes in cardiovascular medicine, propelled by the swift advancements in artificial intelligence (AI). The present work provides an overview of the current applications and challenges of AI in the field of heart failure. It emphasizes the “garbage in, garbage out” issue, where AI systems can produce inaccurate results with skewed data. The discussion covers issues in heart failure diagnostic algorithms, particularly discrepancies between existing models. Concerns about the reliance on the left ventricular ejection fraction (LVEF) for classification and treatment are highlighted, showcasing differences in current scientific perceptions. This review also delves into challenges in implementing AI, including variable considerations and biases in training data. It underscores the limitations of current AI models in real-world scenarios and the difficulty in interpreting their predictions, contributing to limited physician trust in AI-based models. The overarching suggestion is that AI can be a valuable tool in clinicians’ hands for treating heart failure patients, as far as existing medical inaccuracies have been addressed before integrating AI into these frameworks.

Inflammation is a major component of heart failure (HF), causing peripheral vasculopathy and cardiac remodeling. High levels of circulating inflammatory cytokines in HF patients have been well recognized. The hallmark of the inflammatory imbalance is the insufficient production of anti-inflammatory mediators, a condition that leads to dysregulated cytokine activity. The condition progresses because of the pathogenic consequences of the cytokine imbalance, including the impact of endothelial dysfunction and adrenergic responsiveness deterioration, and unfavorable inotropic effects on the myocardium. Hence, to develop possible anti-inflammatory treatment options that will enhance the outcomes of HF patients, it is essential to identify the potential pathophysiological mechanisms of inflammation in HF. Inflammatory mediators, such as cytokines, adhesion molecules, and acute-phase proteins, are elevated during this process, highlighting the complex association between inflammation and HF. Therefore, these inflammatory markers can be used in predicting prognosis of the syndrome. Various immune cells impact on myocardial remodeling and recovery. They lead to stimulation, release of alarmins and risk-related molecule patterns. Targeting key inflammatory mechanisms seems a quite promising therapy strategy in HF. Cytokine modulation is only one of several possible targets in the fight against inflammation, as the potential molecular targets for therapy in HF include immune activation, inflammation, oxidative stress, alterations in mitochondrial bioenergetics, and autophagy.

There is a bidirectional relationship between the heart and the gut. The gut microbiota, the community of gut micro-organisms themselves, is an excellent gut-homeostasis keeper since it controls the growth of potentially harmful bacteria and protects the microbiota environment. There is evidence suggesting that a diet rich in fatty acids can be metabolized and converted by gut microbiota and hepatic enzymes to trimethyl-amine N-oxide (TMAO), a product that is associated with atherogenesis, platelet dysfunction, thrombotic events, coronary artery disease, stroke, heart failure (HF), and, ultimately, death. HF, by inducing gut ischemia, congestion, and, consequently, gut barrier dysfunction, promotes the intestinal leaking of micro-organisms and their products, facilitating their entrance into circulation and thus stimulating a low-grade inflammation associated with an immune response. Drugs used for HF may alter the gut microbiota, and, conversely, gut microbiota may modify the pharmacokinetic properties of the drugs. The modification of lifestyle based mainly on exercise and a Mediterranean diet, along with the use of pre- or probiotics, may be beneficial for the gut microbiota environment. The potential role of gut microbiota in HF development and progression is the subject of this review.

Introduction: Aging, cardiovascular disease (CVD), and heart failure (HF) increase the coexisting morbidity (CM) burden. This study compared the contribution of HF with this increase in elderly patients hospitalized for CVD by comparing patients with and without HF. Methods: Consecutive patients aged >65 years, hospitalized with CVD, were included (104 with and 100 without HF). The prevalence of 10 common CM (hypertension, coronary artery disease, atrial fibrillation, diabetes, dyslipidemia, anemia, chronic kidney disease, chronic obstructive pulmonary disease, sleep apnea, and cancer) was examined. The CM burden was assessed with the CM index (number of CM/patient) and multimorbidity (≥2 CM/patient). Results: The CM index was significantly higher [5 (3-6) vs. 3 (2-4), p

Sodium–glucose cotransporter-2 inhibitors (SGLT2is) are a relatively new class of antidiabetic drugs that have shown favorable effects in heart failure (HF) patients, irrespective of the left ventricular ejection fraction (LVEF). Recent studies have demonstrated the beneficial effects of empagliflozin on cardiac function and structure; however, less is known about dapagliflozin. The purpose of the current work was to investigate the association between the use of dapagliflozin and cardiac biomarkers as well as the cardiac structure in a cohort of patients with HF and diabetes mellitus (DM). The present work was an observational study that included 118 patients (dapagliflozin group n = 60; control group n = 58) with HF and DM. The inclusion criteria included: age > 18 years, a history of DM and HF, regardless of LVEF, and hospitalization for HF exacerbation within the previous 6 months. The exclusion criteria were previous treatment with SGLT2i or glucagon-like peptide-1 receptor agonists, a GFR< 30 and life expectancy < 1 year. The evaluation of patients (at baseline, 6 and 12 months) included a clinical assessment, laboratory blood tests and echocardiography. The Mann–Whitney test was used for the comparison of continuous variables between the two groups, while Friedman’s analysis of variance for repeated measures was used for the comparison of continuous variables. Troponin (p < 0.001) and brain natriuretic peptide (BNP) (p < 0.001) decreased significantly throughout the follow-up period in the dapagliflozin group, but not in the control group (p > 0.05 for both). The LV end-diastolic volume index (p < 0.001 for both groups) and LV end-systolic volume index (p < 0.001 for both groups) decreased significantly in the dapagliflozin and the control group, respectively. The LVEF increased significantly (p < 0.001) only in the dapagliflozin group, whereas the global longitudinal strain (GLS) improved in the dapagliflozin group (p < 0.001) and was impaired in the control group (p = 0.021). The left atrial volume index decreased in the dapagliflozin group (p < 0.001) but remained unchanged in the control group (p = 0.114). Lastly, the left ventricular mass index increased significantly both in the dapagliflozin (p = 0.003) and control group (p = 0.001). Dapagliflozin, an SGLT2i, was associated with a reduction in cardiac biomarkers and with reverse cardiac remodeling in patients with HF and DM.

In heart failure (HF) with reduced ejection fraction (HFrEF), four classes of drugs (β-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor neprilysin inhibitors, mineralocorticoid receptor antagonists, and the most recent Sodium–Glucose Co-Transporters 2 Inhibitors) have demonstrated positive results in randomized controlled trials (RCTs). Nevertheless, the latest RCTs are not proper for comparison since they were carried out at various times with dissimilar background therapies and the patients enrolled did not have the same characteristics. The difficulty of extrapolating from these trials and proposing a common framework appropriate for all cases is thus obvious. Despite the fact that these four agents are now the fundamental pillars of HFrEF treatment, the built-up algorithm of initiation and titration is a matter of debate. Electrolyte disturbances are common in HFrEF patients and can be attributed to several factors, such as the use of diuretics, renal impairment, and neurohormonal activation. We have identified several HFrEF phenotypes according to their sodium (Na+) and potassium (K+) status in a “real world” setting and suggest an algorithm on how to introduce the most appropriate drug and set up therapy based on the patients’ electrolytes and the existence of congestion.

Abstract Aims The relative impact of each individual coexisting morbidity on the pathogenesis of heart failure (HF) is incompletely understood. This study aimed to evaluate the prevalence of individual cardiac and non‐cardiac coexisting morbidities both in the overall HF population and in the subgroup of HF patients with a single coexisting morbidity, stratified by left ventricular ejection fraction (LVEF) categories, as a measure of the relative contribution of each co‐morbidity to the pathogenesis of HF. Methods and results This is a prospective, observational study, in which unselected ambulatory patients with chronic HF visiting the HF clinic of a tertiary university hospital from January 2016 to January 2019 were classified according to baseline LVEF into three groups: (i) LVEF

Heart failure (HF) is categorized arbitrarily based on the left ventricular ejection fraction (LVEF) in HF with reduced (HFrEF; LVEF < 40%), mildly reduced (HFmrEF; LVEF 40–49%), or preserved ejection fraction (HFpEF; LVEF ≥ 50%). In this opinion paper, based on (patho)physiological considerations, we contend that the neurohormonal overactivity syndrome (NOHS), which is present in all symptomatic HF patients irrespective of their LVEF, not only contributes to the development of signs and symptoms but it is also a major determinant of patients’ outcomes. In this regard, NHOS is the only currently available treatment target in HF and should be combatted in most patients with the combined use of diuretics and neurohormonal inhibitors (β-blockers, angiotensin receptor-neprilysin inhibitor/angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, mineralocorticoid antagonists, and sodium-glucose co-transporter 2 inhibitors). Unfortunately, despite the advances in therapeutics, HF mortality remains high. Probably machine learning approaches could better assess the multiple and higher-dimension interactions leading to the HF syndrome and define clusters of HF treatment efficacy.

Background Left ventricular assist device (LVAD) thrombosis is clinically devastating and impacts the cost effectiveness of LVAD therapy for advanced heart failure. Anticoagulation and antiplatelet therapies represent the standard of care to mitigate LVAD thrombosis. Phosphodiesterase type 5 inhibitors (PDE‐5is) exhibit hemodynamic, antiplatelet, and antithrombotic effects. Using a national registry, we examined the relationship of PDE‐5i use on thrombotic events in patients with continuous‐flow LVADs. Methods and Results We obtained data from 13 772 patients with continuous flow LVADs participating in a national registry. Patients implanted with primary LVADs from 2012 to 2017 were included in the analysis. The primary end point was a composite of LVAD thrombosis and ischemic stroke. Patients were analyzed according to any use of PDE‐5i after LVAD implantation (PDE‐5i group) versus no use after LVAD implantation (no PDE‐5i group). The primary end point was significantly lower in the PDE‐5i group compared with the no PDE‐5i group (hazard ratio [HR], 0.84; 95% CI, 0.77–0.91; P

Abstract Background Red blood cell distribution width (RDW) is an established prognostic marker in acute and chronic heart failure (HF). Recent studies have pointed out a link among RDW, diabetes mellitus (DM) and inflammation. We sought to investigate the prognostic value and longitudinal pattern of RDW in patients with concomitant HF and DM, which remains unknown. Methods A total of 218 patients (71 diabetics) who presented with acute HF had RDW measured at admission, discharge and 4, 8 and 12 months post-discharge. The study endpoint was all-cause mortality or rehospitalization for HF during 1-year follow-up. Results The study endpoint was met in 33 patients (46.5%) with DM and in 54 patients (36.7%) without DM. RDW at admission was associated with higher event rate both in HF patients with and without DM (adjusted HR: 1.349, p = 0.002, 95% CI 1.120–1.624 and adjusted HR: 1.142, p = 0.033, 95% CI 1.011–1.291 respectively). In addition, a significant interaction was found between diabetes and RDW longitudinal changes (βinteraction = −0.002; SE = 0.001; p = 0.042). Conclusions Despite the similar prognostic significance of RDW in diabetic and non-diabetic HF patients regarding the study endpoint, longitudinal changes were found to be significantly different between these two groups of HF patients. This might be due to the higher inflammatory burden that diabetic HF patients carry and may provide new insights to the pathophysiological mechanism of RDW increase in HF, which remains unknown.

The left ventricular (LV) ejection fraction (LVEF), despite its severe limitations, has had an epicentral role in heart failure (HF) classification, management, and risk stratification for decades. The major argument favoring the LVEF based HF classification has been that it defines groups of patients in which treatment is effective. However, this reasoning has recently collapsed, since medical treatment with neurohormonal inhibitors, has proved beneficial in most HF patients regardless of the LVEF. In addition, there has been compelling evidence, that the LVEF provides poor guidance for device treatment of chronic HF (implantation of cardioverter defibrillator, cardiac resynchronization therapy) since sudden cardiac death may occur and cardiac dyssynchronization may be disastrous in all HF patients. The same holds true for LV assist device implantation, in which the LVEF has been used as a surrogate for LV size. In this review article we update the evidence questioning the use of LVEF-based HF classification and argue that guidance of chronic HF treatment should transition to more contemporary concepts. Specifically, we propose an etiologic chronic HF classification predominantly based on epidemiological data, which will be foundational for further higher resolution phenotyping in the emerging era of precision medicine. [ABSTRACT FROM AUTHOR]

Mechanical circulatory support (MCS) devices are widely used to treat patients with heart failure. Animal studies have been essential to the development of MCS devices. A number of factors must be considered to ensure good results from these experiments. In this review, we discuss current debates on what might be the ideal surgical approach to evaluating MCS devices in large animals, the hemodynamic and laboratory differences between large animals and humans, heart failure models using large animals, and study designs for developing new long-term MCS devices. [ABSTRACT FROM AUTHOR]