1,721,813 research outputs found
Effect of Uptitration of Recommended Heart Failure Medications on Restricted Mean Survival Time in STRONG-HF
Full text linkObesity and inflammation in chronic and acute heart failure
Full text linkObesity and inflammation have been associated with an increased incidence of heart failure (HF) and death. However, until recent years, no therapy directed towards reducing inflammation and reducing obesity has been shown to reduce those adverse outcomes. Over the past few years, a few small studies have suggested that improving obesity—and in even smaller studies, reducing inflammation—may help improve HF severity, congestion, quality of life, and possibly outcomes. Larger studies that are being planned and executed, which will report their results within the next 2–3 years, should help further clarify the effects of weight and inflammation reduction in patients with HF
Reply to "Clinical implications of left atrial changes after optimization of medical therapy in heart failure patients"
Full text linkApplications of artificial intelligence and machine learning in heart failure
No full text: Machine learning (ML) is a sub-field of artificial intelligence that uses computer algorithms to extract patterns from raw data, acquire knowledge without human input, and apply this knowledge for various tasks. Traditional statistical methods that classify or regress data have limited capacity to handle large datasets that have a low signal-to-noise ratio. In contrast to traditional models, ML relies on fewer assumptions, can handle larger and more complex datasets, and does not require predictors or interactions to be pre-specified, allowing for novel relationships to be detected. In this review, we discuss the rationale for the use and applications of ML in heart failure, including disease classification, early diagnosis, early detection of decompensation, risk stratification, optimal titration of medical therapy, effective patient selection for devices, and clinical trial recruitment. We discuss how ML can be used to expedite implementation and close healthcare gaps in learning healthcare systems. We review the limitations of ML, including opaque logic and unreliable model performance in the setting of data errors or data shift. Whilst ML has great potential to improve clinical care and research in HF, the applications must be externally validated in prospective studies for broad uptake to occur
Comparative effectiveness of torsemide versus furosemide in heart failure patients: insights from the PROTECT trial
Full text linkThe authors assessed the comparative effectiveness of torsemide versus furosemide in the PROTECT trial
Rationale and design of a study to evaluate management of proteinuria in patients at high risk for vascular events: the IMPROVE trial
No full textDeclining kidney function predicts increasing cardiovascular risk in people with hypertension. Microalbuminuria is a marker for cardiovascular risk and declining kidney function. Agents that block the renin-angiotensin-aldosterone system (RAAS), notably angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs), reduce proteinuria and microalbuminuria, lower blood pressure and slow the progression of proteinuric kidney disease. Evidence is accumulating that the combination of an ACE inhibitor and an ARB is the optimal means of RAAS blockade in this setting, slowing the progression of nephropathy independently of blood pressure lowering to a greater degree than can be achieved using maximum approved doses of either agent alone. However, the emerging therapeutic potential of ACE inhibitor/ARB combination therapy in hypertensive kidney disease requires further characterization. The Irbesartan in the Management of PROteinuric patients at high risk for Vascular Events trial aims to determine definitively whether the combination therapy of an ARB, irbesartan and an ACE inhibitor, ramipril, is more effective than ramipril alone in reducing the urinary albumin excretion rate in patients at high cardiovascular risk with hypertension and proteinuria or microalbuminuria
A randomized, double-blind, placebo-controlled, multicentre study to assess haemodynamic effects of serelaxin in patients with acute heart failure
Full text linkThe aim of this study was to evaluate the haemodynamic effects of serelaxin (30 μg/kg/day 20-h infusion and 4-h post-infusion period) in patients with acute heart failure (AHF)
Going 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
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