Title Electrocardiographic markers of adverse left ventricular remodeling and myocardial fibrosis in severe aortic stenosis /
Authors Balčiūnaitė, Giedrė ; Rudinskaitė, Ieva ; Palionis, Darius ; Besusparis, Justinas ; Žurauskas, Edvardas ; Janušauskas, Vilius ; Zorinas, Aleksejus ; Valevičienė, Nomeda Rima ; Ručinskas, Kęstutis ; Sogaard, Peter ; Glaveckaitė, Sigita
DOI 10.3390/jcm12175588
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Is Part of Journal of clinical medicine.. Basel : MDPI. 2023, vol. 12, iss. 17, art. no. 5588, p. [1-18].. eISSN 2077-0383
Keywords [eng] aortic stenosis ; cardiovascular magnetic resonance ; electrocardiographic strain ; myocardial fibrosis ; T1 mapping
Abstract [eng] The optimal timing for aortic valve replacement (AVR) in aortic stenosis (AS) is still controversial and may be guided by markers of adverse left ventricular (LV) remodeling. We aim to assess electrocardiographic (ECG) strain in relation to LV remodeling and myocardial fibrosis. 83 severe AS patients underwent surgical AVR, with preoperative 12-lead ECG, cardiovascular magnetic resonance with T1 mapping and echocardiography with global longitudinal strain analysis. Collagen volume fraction (CVF) was measured in myocardial biopsies sampled during AVR. Patients with ECG strain had more severe AS, more advanced LV remodeling and evidence of heart failure. Patients with ECG strain had more diffuse fibrosis, as evident by higher mean native T1 values (974.8 ± 34 ms vs. 946.5 ± 28 ms, p < 0.001). ECG strain was the only predictor of increased LV mass index on multivariate regression analysis (OR = 7.10, 95% CI 1.46–34.48, p = 0.02). Patients with persistent ECG strain at 1 year following AVR had more advanced LV remodeling and more histological fibrosis (CVF 12.5% vs. 7.3%, p = 0.009) at baseline assessment. Therefore, ECG strain is a marker of adverse LV remodeling and interstitial myocardial fibrosis. Lack of improvement in ECG strain following AVR indicates more advanced baseline LV injury and higher levels of myocardial fibrosis.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2023
CC license CC license description