Congestion in heart failure: a circulating biomarker‐based perspective. A review from the Biomarkers Working Group of the Heart Failure Association, European Society of Cardiology

2022

Closed access Metadata (CSL-JSON)
DOI 10.1002/ejhf.2664
Data confidence 85 high
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Congestion is a cardinal sign of heart failure (HF). In the past, it was seen as a homogeneous epiphenomenon that identified patients with advanced HF. However, current evidence shows that congestion in HF varies in quantity and distribution. This updated view advocates for a congestive-driven classification of HF according to onset (acute vs. chronic), regional distribution (systemic vs. pulmonary), compartment of distribution (intravascular vs. extravascular), and clinical vs. subclinical. Thus, this review will focus on the utility of circulating biomarkers for assessing and managing the different fluid overload phenotypes. This discussion focused on the clinical utility of the natriuretic peptides, carbohydrate antigen 125 (also called mucin 16), bio-adrenomedullin and mid-regional pro-adrenomedullin, ST2 (also known as interleukin-1 receptor-like 1), cluster of differentiation 146, troponin, C-terminal pro-endothelin-1, and parameters of haemoconcentration. The utility of circulation biomarkers on top of clinical evaluation, haemodynamics, and imaging needs to be better determined by dedicated studies. Some multiparametric frameworks in which these tools contribute to management are proposed.