1,721,009 research outputs found
Focus on 2023 ESC guidelines for the management of infective endocarditis: In light of new evidence
No full textFrailty, sarcopenia and cachexia in heart failure patients: Different clinical entities of the same painting
Full text linkHeart Failure (HF) in elderly patients is a systemic syndrome where advanced age, comorbidities with organ system deterioration, frailty and impaired cognition significantly impact outcome. Cardiac cachexia, sarcopenia and frailty despite overlap in definitions are different clinical entities that frequently coexist in HF patients. However, these co-factors often remain unaddressed, resulting in poor quality-of-life, prolonged physical disability and exercise intolerance and finally with higher rehospitalization rates and mortality. Strategy aim to increase muscle mass and muscle strength and delay the occurrence of frailty state appear essential in this regard. Common HF drugs therapy (b-blockers, angiotensinconverting enzyme inhibitors) and prescription of physical exercise program remain the cornerstone of therapeutic approach in HF patients with new promising data regarding nutritional supplementation. However, the treatment of all these conditions still remain debated and only a profound knowledge of the specific mechanisms and patterns of disease progression will allow to use the appropriate therapy in a given clinical setting. For all these reasons we briefly review current knowledge on frailty, sarcopenia and cachexia in HF patients with the attempt to define clinically significant degrees of multiorgan dysfunction, specific "red alert"thresholds in clinical practice and therapeutic approach
The Role of the Left Atrium: From Multimodality Imaging to Clinical Practice: A Review
Full text linkIn recent years, new interest is growing in the left atrium (LA). LA functional analysis and measurement have an essential role in cardiac function evaluation. Left atrial size and function are key elements during the noninvasive analysis of diastolic function in several heart diseases. The LA represents a “neuroendocrine organ” with high sensitivity to the nervous, endocrine, and immune systems. New insights highlight the importance of left atrial structural, contractile, and/or electrophysiological changes, introducing the concept of “atrial cardiomyopathy”, which is closely linked to underlying heart disease, arrhythmias, and conditions such as aging. The diagnostic algorithm for atrial cardiomyopathy should follow a stepwise approach, combining risk factors, clinical characteristics, and imaging. Constant advances in imaging techniques offer superb opportunities for a comprehensive evaluation of LA function, underlying specific mechanisms, and patterns of progression. In this literature review, we aim to suggest a practical, stepwise algorithm with integrative multimodality imaging and a clinical approach for LA geometry and functional analysis. This integrates diastolic flow analysis with LA remodelling by the application of traditional and new diagnostic imaging techniques in several clinical settings such as heart failure (HF), atrial fibrillation (AF), coronary artery disease (CAD), and mitral regurgitation (MR)
The Treatment of Heart Failure in Patients with Chronic Kidney Disease: Doubts and New Developments from the Last ESC Guidelines
Full text linkPatients with heart failure (HF) and associated chronic kidney disease (CKD) are a population less represented in clinical trials; additionally, subjects with more severe estimated glomerular filtration rate reduction are often excluded from large studies. In this setting, most of the data come from post hoc analyses and retrospective studies. Accordingly, in patients with advanced CKD, there are no specific studies evaluating the long-term effects of the traditional drugs commonly administered in HF. Current concerns may affect the practical approach to the traditional treatment, and in this setting, physicians are often reluctant to administer and titrate some agents acting on the renin angiotensin aldosterone system and the sympathetic activity. Therefore, the extensive application in different HF subtypes with wide associated conditions and different renal dysfunction etiologies remains a subject of debate. The role of novel drugs, such as angiotensin receptor blocker neprilysin inhibitors and sodium glucose linked transporters 2 inhibitors seems to offer a new perspective in patients with CKD. Due to its protective vascular and hormonal actions, the use of these agents may be safely extended to patients with renal dysfunction in the long term. In this review, we discussed the largest trials reporting data on subjects with HF and associated CKD, while suggesting a practical stepwise algorithm to avoid renal and cardiac complications
The relevance of specific heart failure outpatient programs in the COVID era: An appropriate model for every disease
Full text linkHeart Failure (HF) is characterized by an elevated readmission rate, with almost 50% of events occurring after the first episode over the first 6 months of the post-discharge period. In this context, the vulnerable phase represents the period when patients elapse from a sub-acute to a more stabilized chronic phase. The lack of an accurate approach for each HF subtype is probably the main cause of the inconclusive data in reducing the trend of recurrent hospitalizations. Most care programs are based on the main diagnosis and the HF stages, but a model focused on the specific HF etiology is lacking. The HF clinic route based on the HF etiology and the underlying diseases responsible for HF could become an interesting approach, compared with the traditional programs, mainly based on non-specific HF subtypes and New York Heart Association class, rather than on detailed etiologic and epidemiological data. This type of care may reduce the 30-day readmission rates for HF, increase the use of evidence-based therapies, prevent the exacerbation of each comorbidity, improve patient compliance, and decrease the use of resources. For all these reasons, we propose a dedicated outpatient HF program with a daily practice scenario that could improve the early identification of symptom progression and the quality-of-life evaluation, facilitate the access to diagnostic and laboratory tools and improve the utilization of financial resources, together with optimal medical titration and management
Prediction of Atrial Fibrillation using Deep Learning techniques
No full textAtrial fibrillation (AF) is one of the most prevalent arrhythmias encountered in cardiological practice; it is a leading cause of stroke and heart failure and has a growing financial impact on the healthcare system. The aim of this study is to test the efficacy of deep learning in predicting AF. Early diagnosis can improve patients quality of life, reduce hospitalizations and minimize the financial impact on the health care system. Two methods for automatically predicting AF based on Convolutional Neural Networks (CNN) are proposed. The first model is characterized by a one-dimensional (1D) CNN network that takes, directly, electrocardiogram (ECG) signals as input, while the second model consists of a two dimensional (2D) CNN network that inputs image data corresponding to the numerical values of the most important events associated with each ECG waveform. The 1D-CNN model achieved an accuracy of 71.69%, while the 2D-CNN model reached 76.19%. The second method, in addition of being a novel approach to classification problem, reached a good score in predicting the outcome of atrial fibrillation
Recent knowledges on chemosensitivity to hypoxia and hypercapnia in cardiovascular disease.
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Deep Learning for Predicting Congestive Heart Failure
Full text linkCongestive heart failure (CHF) is one of the most debilitating cardiac disorders. It is a costly disease in terms of both lives and financial outlays, given the high rate of hospital re-admissions and mortality. Heart failure (HF) is notoriously difficult to identify on time, and is frequently accompanied by additional comorbidities that further complicate diagnosis. Many decision support systems (DSS) have been developed to facilitate diagnosis and to raise the standard of screening and monitoring operations, even for non-expert staff. This is confirmed in the literature by records of highly performing diagnosis-aid systems, which are unfortunately not very relevant to expert cardiologists. In order to assist cardiologists in predicting the trajectory of HF, we propose a deep learning-based system which predicts severity of disease progression by employing medical patient history. We tested the accuracy of four models on a labeled dataset, composed of 1037 records, to predict CHF severity and progression, achieving results comparable to studies based on much larger datasets, none of which used longitudinal multi-class prediction. The main contribution of this work is that it demonstrates that a fairly complicated approach can achieve good results on a medium size dataset, providing a reasonably accurate means of determining the evolution of CHF well in advance. This potentially constitutes a significant aid for healthcare managers and expert cardiologists in designing different therapies for medication, healthy lifestyle changes and quality of life (QoL) management, while also promoting allocation of resources with an evidence-based approach. © 2022 by the authors
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