Heart Failure Reviews最新文献

Adrenal insufficiency (AI) is a disorder in which inadequate glucocorticoid and mineralocorticoid hormone production leads to a variety of symptoms, including fatigue, weight loss, and nausea. In some patients with unknown AI, adrenal crisis-induced cardiogenic shock (ACCS) can be the first presentation, resulting in a fatal situation. The ACCS may exhibit unresponsiveness to inotropes and fluid therapy; thus, glucocorticoid administration is the primary vital intervention, making early detection of AI essential. Hence, in this study, we review the case reports demonstrating acute cardiomyopathies in the context of AI. The review addresses the suggested underlying mechanisms, including the diminished protective effects of glucocorticoids against catecholamines in AI. We also highlighted some clues to aid physicians in considering AI as a differential diagnosis in critically ill patients presenting cardiogenic shock.

The clinical and economic impact of heart failure (HF) is immense and will continue to rise due to the increasing prevalence of the disease. Despite the availability of guideline-recommended medications that improve mortality, reduce hospitalizations, and enhance quality of life, there are major gaps in the implementation of such care. Quality improvement interventions have generally focused on clinicians. While certain interventions have had modest success in improving the use of heart failure medications, they remain insufficient in optimizing HF care. Here, we discuss how patient-facing interventions can add value and supplement clinician-centered interventions. We discuss how digital health can be leveraged to create patient activation tools that create a larger, sustainable impact. Small studies have suggested the promise of digital tools for patient engagement and self-care, but there are also important barriers to the adoption of such interventions that we describe. We share key principles and strategies around the design and implementation of digital health innovations to maximize patient participation and engagement. By uniquely activating patients in their own care, digital health can unlock the full potential of both existing and new quality improvement initiatives to drive forward high-quality and equitable heart failure care.

The concept of quadruple therapy as a "one-size-fit-all" approach is effective among all eligible patients with heart failure with reduced ejection fraction, with consistent and significant clinical benefits including reduced mortality across various subgroups. However, with exception of sodium-glucose cotransporter 2 inhibitors, the consistency of benefit with therapies does not extend to patients with heart failure with preserved ejection fraction. The clinical benefits of other promising medical therapies, such as angiotensin receptor-neprilysin inhibitors, mineralocorticoid receptor antagonists, and glucagon-like peptide-1 receptor agonists, have been demonstrated only in certain phenotypes of the highly heterogenous heart failure with preserved ejection fraction population. This variability can confuse frontline practicing cardiologists, potentially leading to the under-implementation of these medications. Therefore, we propose a simple approach: "targeted" combination therapy. This strategy aims to optimize evidence-based medications in heart failure with preserved ejection fraction by tailoring treatments to specific subgroups within the heart failure with preserved ejection fraction population where significant benefits are most evident.

Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study, guided by PRISMA guidelines, explores the expanding role of artificial intelligence (AI) in myocarditis, aiming to consolidate current knowledge and guide future research. Following PRISMA guidelines, a systematic review was conducted across PubMed, Cochrane Reviews, Scopus, Embase, and Web of Science databases. MeSH terms including artificial intelligence, deep learning, machine learning, myocarditis, and inflammatory cardiomyopathy were used. Inclusion criteria involved original articles utilizing AI for myocarditis, while exclusion criteria eliminated reviews, editorials, and non-AI-focused studies. The search yielded 616 articles, with 42 meeting inclusion criteria after screening. The identified articles, spanning diagnostic, survival prediction, and molecular analysis aspects, were analyzed in each subsection. Diagnostic studies showcased the versatility of AI algorithms, achieving high accuracies in myocarditis detection. Survival prediction models exhibited robust discriminatory power, particularly in emergency settings and pediatric populations. Molecular analyses demonstrated AI's potential in deciphering complex immune interactions. This systematic review provides a comprehensive overview of AI applications in myocarditis, highlighting transformative potential in diagnostics, survival prediction, and molecular understanding. Collaborative efforts are crucial for overcoming limitations and realizing AI's full potential in improving myocarditis care.

Increased sympathetic and reduced parasympathetic nerve activity is associated with disease progression and poor outcomes in patients with chronic heart failure. The demonstration that markers of autonomic imbalance and vagal dysfunction, such as reduced heart rate variability and baroreflex sensitivity, hold prognostic value in patients with chronic heart failure despite modern therapies encourages the research for neuromodulation strategies targeting the vagus nerve. However, the approaches tested so far have yielded inconclusive results. This review aims to summarize the current knowledge about the role of the parasympathetic nervous system in chronic heart failure, describing the pathophysiological background, the methods of assessment, and the rationale, limits, and future perspectives of parasympathetic stimulation either by drugs or bioelectronic devices.

Diuresis to achieve decongestion is a central aim of therapy in patients hospitalized for acute decompensated heart failure (ADHF). While multiple approaches have been tried to achieve adequate decongestion rapidly while minimizing adverse effects, no single diuretic strategy has shown superiority, and there is a paucity of data and guidelines to utilize in making these decisions. Observational cohort studies have shown associations between urine sodium excretion and outcomes after hospitalization for ADHF. Urine chemistries (urine sodium ± urine creatinine) may guide diuretic titration during ADHF, and multiple randomized clinical trials have been designed to compare a strategy of urine chemistry-guided diuresis to usual care. This review will summarize current literature for diuretic monitoring and titration strategies, outline evidence gaps, and describe the recently completed and ongoing clinical trials to address these gaps in patients with ADHF with a particular focus on the utility of urine sodium-guided strategies.

Clinical congestion remains a major cause of hospitalization and re-hospitalizations in patients with chronic heart failure (HF). Despite the high prevalence of this issue and clinical concern in HF practice, there is limited understanding of the complex pathophysiology relating to the "congestion" of congestive HF. There is no unifying definition or clear consensus on what is meant or implied by the term "congestion." Further, the discordance in study findings relating congestion to physical signs and symptoms of HF, cardiac hemodynamics, or metrics of weight change or fluid loss with diuretic therapy has not added clarity. In this review, these factors will be discussed to add perspective to this issue and consider the factors driving "congestion." There remains a need to better understand the roles of fluid retention promoting intravascular and interstitial compartment expansions, blood volume redistribution from venous reservoirs, altered venous structure and capacity, elevated cardiac filling pressure hemodynamics, and heterogeneous intravascular volume profiles (plasma volume and red blood cell mass) with a goal to help demystify "congestion" in HF. Further, this includes highlighting the importance of recognizing that congestion is not the result of a single pathway but a complex of responses some of which produce symptoms while others do not; yet, we confine these varied responses to the single and somewhat vague term "congestion."

Congenital heart disease (CHD) is the most common global congenital defect affecting over 2.4 million individuals in the United States. Ongoing medical and surgical advancements have improved the survival of children with CHD leading to a shift where, as of 2010, adults constitute two-thirds of the CHD patient population. The increasing number and aging of adult congenital heart disease (ACHD) patients present a clinical challenge due to heightened complexity, morbidity, and mortality. Studies indicate that 1 in 13 ACHD patients will develop heart failure (HF) in their lifetime. ACHD-HF patients experience more frequent emergency department visits, higher hospitalization rates, longer hospital stays, and higher mortality compared to non-ACHD patients with heart failure (non-ACHD-HF). Despite HF being the leading cause of death in ACHD patients, there is a notable gap in evidence regarding treatment. While guideline-directed medical therapy (GDMT) has been extensively studied in non-ACHD-HF, research specific to ACHD-HF individuals is limited. This article aims to comprehensively review available literature addressing the pharmacological treatment of ACHD-HF.

Cardiovascular disease is a major non-communicable disease globally, with increasing prevalence, posing a significant public health challenge. It is the leading non-obstetric cause of perinatal morbidity and mortality, with a substantial number of cardiac fatalities occurring in individuals without any known pre-existing cardiovascular disease. Peripartum cardiomyopathy is a type of de novo heart failure that occurs in pregnant women in the late stages of pregnancy or following delivery. Despite extensive research, diagnosing and managing peripartum cardiomyopathy remains challenging, resulting in significant morbidity and mortality. Recent advancements and novel approaches have been made to better understand and manage peripartum cardiomyopathy, including molecular and non-molecular biomarkers, genetic predisposition and risk prediction, targeted therapies, multidisciplinary care, and improved patient education. This narrative review provides a comprehensive overview and new perspectives on peripartum cardiomyopathy, covering its epidemiology, updated pathophysiological mechanisms, diagnosis, management, and future research directions for healthcare professionals, researchers, and clinicians.