Abstract
OBJECTIVE: To investigate the relationship between quantitative parameters of echocardiography and vascular endothelial function in patients with chronic heart failure (CHF) and the predictive value of short-term major adverse cardiovascular events (MACE). METHODS: From February 2018 to February 2020, 86 CHF patients in our hospital were selected as the observation group, and 46 healthy subjects were selected as the control group during the same period. Quantitative parameters of echocardiography (left ventricular ejection fraction (LVEF), left ventricular short-axis shortening rate (FS), and ratio of peak flow velocity between early and late mitral valve diastole (E/A)) and endothelial function indexes (endothelin-1 (ET-1)/nitric oxide (NO)) were compared between the two groups. The correlation between quantitative parameters of echocardiography and vascular endothelial function in patients with CHF was analyzed. A logistic regression equation was used to analyze the risk factors of MACE in patients with CHF. The receiver operating characteristic curve (ROC) was used to analyze the predictive value of quantitative parameters of echocardiography and NO/ET-1 for the risk of MACE in patients with CHF. RESULT: LVEF, FS, and NO/ET-1 in the observation group were lower than those in the control group, while E/A was higher than that in the control group (P < 0.05). In CHF patients, LVEF and FS were positively correlated with NO/ET-1, while E/A was negatively correlated with NO/ET-1 (P < 0.05). Logistic regression analysis showed that the decrease of LVEF, FS, NO/ET-1, and E/A were risk factors for MACE (P < 0.05) after adjusting for age, body mass index, and cardiac function grading. The AUC value of short-term MACE predicted by quantitative parameters of echocardiography and NO/ET-1 combined was 0.883, with a corresponding sensitivity of 86.21% and specificity of 73.13%. CONCLUSION: Quantitative parameters of echocardiography in CHF patients are related to vascular endothelial function, and their combination can effectively predict the risk of MACE in the near future, providing reference for clinical treatment.