Heart failure (HF) is a complex syndrome caused by a variety of structural or functional cardiac abnormalities as a consequence of several involved pathophysiological pathways. In the last decades, left ventricular ejection fraction (LVEF) has represented the principal criterion used to stratify HF, to interpret ventricular function and to identify therapeutic strategies. However, this chimeric parameter oversimplifies the multiple pathways and mechanisms underlying the progression of HF. Indeed, HF should be more appropriately considered as the final stage of multiple disease states, characterized by distinct phenotypes on the basis of key clinical and molecular variables, such as underlying etiologies and conditions, demographic and structural features and specific biomarkers. Accordingly, HF should be viewed as a continuous spectrum in which the specific phenotypes need to be accurately identified with the aim to improve the disease management with a more tailored approach. In such a complex and heterogeneous scenario, the clinical benefits of an angiotensin receptor neprilysin inhibition strategy, namely in the single pill sacubitril/valsartan (S/V), have been shown across the entire HF continuum, representing a fundamental therapeutic strategy, although with different magnitudes depending on the severity and the stage of the clinical syndrome. In this viewpoint paper we have reconsidered the role of S/V in the light of different HF phenotypes and on the basis of HF considered as a whole spectrum.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419408 | PMC |
http://dx.doi.org/10.3389/fphys.2021.652163 | DOI Listing |
Acta Pharm
December 2024
Department of Clinical Pharmacy, University Hospital Dubrava, 10000 Zagreb Croatia.
Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity globally. It is estimated that 17.9 million people died from CVDs in 2019, which represents 32 % of all deaths worldwide.
View Article and Find Full Text PDFEur Heart J Cardiovasc Imaging
January 2025
Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy.
Aim: Computed tomography (CT)-derived extracellular volume fraction (ECV) is a non-invasive method to quantify myocardial fibrosis. Evaluating CT-ECV during aortic valve replacement (AVR) planning CT in severe aortic stenosis (AS) may aid prognostic stratification. This meta-analysis evaluated the prognostic significance of CT-ECV in severe AS necessitating AVR.
View Article and Find Full Text PDFASAIO J
December 2024
Cleveland Clinic Florida, Heart, Vascular and Thoracic Institute, Advanced Heart Failure Program, Weston, Florida.
We investigated the association of preimplant left ventricular end-diastolic diameter (LVEDD) with outcomes after HeartMate 3 (HM3) left ventricular assist device (LVAD) implantation. Patients from the European Registry for Patients with Mechanical Circulatory Support (EUROMACS) registry who underwent HM3 implantation from August 2014 to February 2023 (n = 834) were analyzed according to preoperative LVEDD: less than or equal to 65 (n = 251), 65-80 (n = 441), and greater than or equal to 80 mm (n = 142). The mean age was 54.
View Article and Find Full Text PDFJ Clin Endocrinol Metab
January 2025
Department of Neurosurgery and State Key Laboratory of Trauma, Burn and Combined Injury, Southwest Hospital; Chongqing Key Laboratory of Precision Neuromedicine and Neuroregenaration, Third Military Medical University (Army Medical University), 400038 Chongqing, China.
Background: Phthalates, widely used as chemical additives, are often found as mixtures in the environment. However, the combined impact of phthalate exposure on sarcopenia remains unclear.
Objective: This study aimed to investigate the relationships between phthalates and sarcopenia in adults.
Eur Heart J Acute Cardiovasc Care
January 2025
Department of Medical Informatics, Korea University College of Medicine, Seoul, Republic of Korea.
Background: Acute heart failure (AHF) poses significant diagnostic challenges in the emergency room (ER) because of its varied clinical presentation and limitations of traditional diagnostic methods. This study aimed to develop and evaluate a deep-learning model using electrocardiogram (ECG) data to enhance AHF identification in the ER.
Methods: In this retrospective cohort study, we analyzed the ECG data of 19,285 patients who visited ERs of three hospitals between 2016 and 2020; 9,119 with available left ventricular ejection fraction and N-terminal prohormone of brain natriuretic peptide level data and who were diagnosed with AHF were included in the study.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!