Abstract
This study aimed to investigate the predictive value of Big endothelin-1(ET-1) for left ventricular reverse remodeling (LVRR) and prognosis in patients with dilated cardiomyopathy (DCM). Patients with DCM and a left ventricular ejection fraction (LVEF) ≤ 50% from 2008 to 2017 were included. LVRR was defined as the LVEF increased by at least 10% or follow-up LVEF increased to at least 50% with a minimum improvement of 5%; meanwhile, the index of left ventricular end-diastolic diameter (LVEDDi) decreased by at least 10% or LVEDDi decreased to ≤33 mm/m2. The composite outcome for prognostic analysis consisted of death and heart transplantations. Of the 375 patients included (median age 47 years, 21.1% female), 135 patients (36%) had LVRR after a median of 14 months of treatment. An independent association was found between Big ET-1 at baseline and LVRR in the multivariate model (OR 0.70, 95% CI 0.55–0.89, p = 0.003, per log increase). Big ET-1, body mass index, systolic blood pressure, diagnosis of type 2 diabetes mellitus (T2DM) and treatment with ACEI/ARB were significant predictors for LVRR after stepwise selection. Adding Big ET-1 to the model improved the discrimination (∆AUC = 0.037, p = 0.042 and reclassification (IDI, 3.29%; p = 0.002; NRI, 35%; p = 0.002) for identifying patients with LVRR. During a median follow-up of 39 (27–68) months, Big ET-1 was also independently associated with the composite outcome of death and heart transplantations (HR 1.45, 95% CI 1.13–1.85, p = 0.003, per log increase). In conclusion, Big ET-1 was an independent predictor for LVRR and had prognostic implications, which might help to improve the risk stratification of patients with DCM.
Author supplied keywords
Cite
CITATION STYLE
Feng, J., Liang, L., Chen, Y., Tian, P., Zhao, X., Huang, B., … Zhang, J. (2023). Big Endothelin-1 as a Predictor of Reverse Remodeling and Prognosis in Dilated Cardiomyopathy. Journal of Clinical Medicine, 12(4). https://doi.org/10.3390/jcm12041363
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.