Increased Entropy Predicts Adverse Cardiac Events in Patients with High Cardiovascular Risk and Hypertension: A Novel Imaging Parameter Derived from Late Gadolinium Enhancement
Background: Entropy derived from late gadolinium enhancement (LGE) has been shown to correlate with major adverse cardiac events (MACEs) in various cardiac diseases. However, the association between myocardial entropy and MACEs in patients with hypertension (HTN) has not been repo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IMR Press
2025-05-01
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| Series: | Reviews in Cardiovascular Medicine |
| Subjects: | |
| Online Access: | https://www.imrpress.com/journal/RCM/26/5/10.31083/RCM26499 |
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| Summary: | Background: Entropy derived from late gadolinium enhancement (LGE) has been shown to correlate with major adverse cardiac events (MACEs) in various cardiac diseases. However, the association between myocardial entropy and MACEs in patients with hypertension (HTN) has not been reported. Methods: This study recruited 190 patients with high cardiovascular risk and essential HTN who underwent cardiac magnetic resonance (CMR) examination in our hospital between January 2020 and June 2024. HTN patients were followed up for MACEs, which were defined as hospitalization for the occurrence of heart failure, acute coronary syndromes, stroke, or all-cause death. Patients were divided into MACE and non-MACE groups. Cardiac morphology, function, and tissue characteristics were assessed using CMR, and left ventricular (LV) entropy was acquired from LGE images. Results: Of the 190 patients with HTN, 54 (28.4%) experienced a MACE over a median follow-up period of 12.0 (8.0–27.0) months. LV entropy was significantly higher in patients with MACEs than those without (5.75 ± 0.89 vs. 5.12 ± 1.26; p < 0.001). Furthermore, LV entropy was an independent predictor of MACE, even after adjustment for clinical risk factors (odds ratio: 1.569 (1.039–2.369); p = 0.032). Receiver operating characteristic curve (ROC) analysis showed the predictive value of LV entropy, with an area under the curve (AUC) of 0.663. Adding LV entropy to the clinical model resulted in a relatively higher AUC (0.813 vs. 0.806) for the prediction of MACEs; however, this was not significantly different from the clinical model alone (p = 0.570). Conclusions: HTN patients with MACEs presented higher LV entropy than patients without MACEs. Furthermore, as an independent predictor of MACEs, LV entropy may help the risk stratification of HTN patients with high cardiovascular risk. Clinical Trial Registration: ChiCTR2100049160, https://www.chictr.org.cn/showproj.html?proj=130381. |
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| ISSN: | 1530-6550 |