Affiliation:
1. Department of Echocardiography, Zhongshan Hospital Fudan University Shanghai China
2. Shanghai Institute of Cardiovascular Diseases Shanghai China
3. Shanghai Institute of Medical Imaging Shanghai China
4. Department of Nephrology, Zhongshan Hospital Fudan University Shanghai China
5. Department of Radiology, Zhongshan Hospital Fudan University Shanghai China
Abstract
AbstractBackgroundThe application value of myocardial work (MW) in evaluating myocardial function and predicting major adverse cardiovascular events (MACE) in maintenance hemodialysis (MHD) patients has not been fully explored.PurposeComparing noninvasive MW parameters between MHD patients and healthy controls, and further determining its value in predicting MACE in MHD patients.MethodsA prospective single‐institution study included 92 MHD patients without prior cardiovascular disease and 40 age‐ and sex‐matched healthy controls. Conventional echocardiographic data, global longitudinal strain (GLS), and MW parameters (global work index [GWI], global constructive work [GCW], global work efficiency [GWE], global wasted work [GWW]) were derived and compared between MHD and the control. Logistic regression was used to determine the predictive value of these parameters for MACE. The receiver operating characteristic curve was utilized to compare the predictive differences of MACE between GWE and GLS.ResultsCompared with healthy individuals, MHD patients had significantly reduced GWE, GLS and elevated LVMI, GWW (all p < 0.001), while there was no significant difference in left ventricular ejection fraction. Twenty eight (30%) MHD patients experienced MACE. Two nested models adding GWE and GLS, respectively, showed that age (p < 0.005), GWE (p = 0.034), and GLS (p = 0.014) were independent predictors of MACE. The AUC derived from GWE for predicting MACE was significantly higher than that derived from GLS (0.836 vs. 0.743, p = 0.039).ConclusionsMyocardial work is a novel tool for assessing left ventricular myocardial performance in MHD patients. GWE is an independent predictor of MACE.
Funder
National Natural Science Foundation of China