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Identification of patients with nonischemic dilated cardiomyopathy at risk of malignant ventricular arrhythmias: insights from cardiac magnetic resonance feature tracking

Authors :
Hai-Yan Ma
Guang-You Xie
Jian Tao
Zong-Zhuang Li
Pan Liu
Xing-Ju Zheng
Rong-Pin Wang
Source :
BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-10 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Background Patients with nonischemic dilated cardiomyopathy (NIDCM) are prone to arrhythmias, and the cause of mortality in these patients is either end-organ dysfunction due to pump failure or malignant arrhythmia-related death. However, the identification of patients with NIDCM at risk of malignant ventricular arrhythmias (VAs) is challenging in clinical practice. The aim of this study was to evaluate whether cardiovascular magnetic resonance feature tracking (CMR-FT) could help in the identification of patients with NIDCM at risk of malignant VAs. Methods A total of 263 NIDCM patients who underwent CMR, 24-hour Holter electrocardiography (ECG) and inpatient ECG were retrospectively evaluated. The patients with NIDCM were allocated to two subgroups: NIDCM with VAs and NIDCM without VAs. From CMR-FT, the global peak radial strain (GPRS), global longitudinal strain (GPLS), and global peak circumferential strain (GPCS) were calculated from the left ventricle (LV) model. We investigated the possible predictors of NIDCM combined with VAs by univariate and multivariate logistic regression analyses. Results The percent LGE (15.51 ± 3.30 vs. 9.62 ± 2.18, P 10.37% are independent predictors of NIDCM combined with VAs.

Details

Language :
English
ISSN :
14712261
Volume :
24
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Cardiovascular Disorders
Publication Type :
Academic Journal
Accession number :
edsdoj.55cc6918914247c1964611b7b2095350
Document Type :
article
Full Text :
https://doi.org/10.1186/s12872-023-03655-4