Heart failure with preserved ejection fraction: Calculating the risk of future heart failure events and death.

Objective: We sought to develop a clinical model to identify heart failure patients with preserved ejection fraction (HFpEF) at highest risk for acute HF events or death.

Methods And Results: Between 2010 and 2019, 422 patients with HFpEF were followed. Acute HF events occurred in 190 patients (45%), including 110 (58%) with recurrent hospitalizations.

Machine learning-derived electrocardiographic algorithm for the detection of cardiac amyloidosis.

Background: Diagnosis of cardiac amyloidosis (CA) requires advanced imaging techniques. Typical surface ECG patterns have been described, but their diagnostic abilities are limited.

Objective: The aim was to perform a thorough electrophysiological characterisation of patients with CA and derive an easy-to-use tool for diagnosis.

Renin Feedback Is an Independent Predictor of Outcome in HFpEF.

Drugs which interact with the renin angiotensin aldosterone system (RAAS) aim to reduce the negative effects of angiotensin (Ang) II. Treatment with these drugs anticipate a compensatory up-regulation of renin; however, it has been shown that there is a large variability in circulating plasma renin (PRA), even in patients with optimal medical therapy in patients with heart failure (HF) with reduced ejection fraction (HFrEF). Our aim was to measure plasma renin activity (PRA-S), its response to RAAS inhibitor (RAASi) therapies and its effects on outcome in patients with HF with preserved ejection fraction (HFpEF).

What Type of Patients Did PARAGON-HF Select? Insights from a Real-World Prospective Cohort of Patients with Heart Failure and Preserved Ejection Fraction.

The PARAGON-HF clinical trial suggested that sacubitril/valsartan may become a treatment option for particular subgroups of patients with heart failure and preserved ejection fraction (HFpEF). However, the proportion of real-world HFpEF patients who are theoretically superimposable with the PARAGON-HF population is yet unknown. The present study was performed to define the proportion of real-world PARAGON-HF-like patients and to describe their clinical characteristics and long-term prognosis in comparison with those who would not meet PARAGON-HF criteria.

Prognostic implications of pericardial and pleural effusion in patients with cardiac amyloidosis.

Background: Pericardial and pleural effusion are common findings in patients with cardiac amyloidosis (CA). It is not known, whether effusions correlate with right ventricular (RV) function in these patients. Furthermore, data on the prognostic significance of pleural and pericardial effusion in CA is scarce.

Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study.

(1) Background: Cardiac amyloidosis (CA) is a rare and complex condition with poor prognosis. While novel therapies improve outcomes, many affected individuals remain undiagnosed due to a lack of awareness among clinicians. This study was undertaken to develop an expert-independent machine learning (ML) prediction model for CA relying on routinely determined laboratory parameters.

Hemodynamic Profiles and Their Prognostic Relevance in Cardiac Amyloidosis.

This study sought to characterize cardiac amyloidosis (CA) patients with respect to hemodynamic parameters and asses their prognostic impact in different CA cohorts. Intracardiac and pulmonary arterial pressures (PAPs) are among the strongest predictors of outcomes in patients with heart failure (HF). Despite that, the hemodynamic profiles of patients with CA and their relation to prognosis have rarely been investigated.

Patients with Heart Failure and Preserved Ejection Fraction Are at Risk of Gastrointestinal Bleeding.

Aims: Two thirds of patients with heart failure and preserved ejection fraction (HFpEF) have an indication for oral anticoagulation (OAC) to prevent thromboembolic events. However, evidence regarding the safety of OAC in HFpEF is limited. Therefore, our aim was to describe bleeding events and to find predictors of bleeding in a large HFpEF cohort.