Berezin AE, Berezina TA, Hoppe UC, Lichtenauer M, Berezin AA. Methods to predict heart failure in diabetes patients.
Expert Rev Endocrinol Metab 2024;
19:241-256. [PMID:
38622891 DOI:
10.1080/17446651.2024.2342812]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 04/10/2024] [Indexed: 04/17/2024]
Abstract
INTRODUCTION
Type 2 diabetes mellitus (T2DM) is one of the leading causes of cardiovascular disease and powerful predictor for new-onset heart failure (HF).
AREAS COVERED
We focus on the relevant literature covering evidence of risk stratification based on imaging predictors and circulating biomarkers to optimize approaches to preventing HF in DM patients.
EXPERT OPINION
Multiple diagnostic algorithms based on echocardiographic parameters of cardiac remodeling including global longitudinal strain/strain rate are likely to be promising approach to justify individuals at higher risk of incident HF. Signature of cardiometabolic status may justify HF risk among T2DM individuals with low levels of natriuretic peptides, which preserve their significance in HF with clinical presentation. However, diagnostic and predictive values of conventional guideline-directed biomarker HF strategy may be non-optimal in patients with obesity and T2DM. Alternative biomarkers affecting cardiac fibrosis, inflammation, myopathy, and adipose tissue dysfunction are plausible tools for improving accuracy natriuretic peptides among T2DM patients at higher HF risk. In summary, risk identification and management of the patients with T2DM with established HF require conventional biomarkers monitoring, while the role of alternative biomarker approach among patients with multiple CV and metabolic risk factors appears to be plausible tool for improving clinical outcomes.
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