Heart Failure Treatment and Management

The paper identifies plasma metabolites associated with incident heart failure with reduced (HFrEF) and preserved ejection fraction (HFpEF) using metabolomics and machine learning, finding higher glutamine levels increase risk while omega-3 fatty acids decrease it.

This study shows low-dose GLP-1RA therapy improves cardiac and hepatic function in HFpEF without weight loss, through mechanisms like reduced fibrosis and lipid accumulation.

The paper uses random survival forests to identify 33 myocardial genes predictive of survival in HFpEF, outperforming clinical parameters in prognosis modeling.

The paper identifies four genes as potential biomarkers for early detection of acute decompensated heart failure caused by venous congestion using bioinformatics and machine learning.

This study uses AI and mass spectrometry to identify biomarkers distinguishing HFpEF and HFrEF patients using the Total Protein Approach.

The paper investigates the association between ADRB1 gene polymorphisms and β-blocker response in CHF patients, finding that Arg389Gly polymorphism correlates with improved cardiac function and prognosis.