Prognostic Value of Right Ventricular Longitudinal Strain in Patients With COVID-19.

ABSTRACT

Objectives: The aim of this study was to investigate whether right ventricular longitudinal strain (RVLS) was independently predictive of higher mortality in patients with coronavirus disease-2019 (COVID-19). Background: RVLS obtained from 2-dimensional speckle-tracking echocardiography has been recently demonstrated to be a more accurate and sensitive tool to estimate right ventricular (RV) function. The prognostic value of RVLS in patients with COVID-19 remains unknown. Methods: One hundred twenty consecutive patients with COVID-19 who underwent echocardiographic examinations were enrolled in our study. Conventional RV functional parameters, including RV fractional area change, tricuspid annular plane systolic excursion, and tricuspid tissue Doppler annular velocity, were obtained. RVLS was determined using 2-dimensional speckle-tracking echocardiography. RV function was categorized in tertiles of RVLS. Results: Compared with patients in the highest RVLS tertile, those in the lowest tertile were more likely to have higher heart rate; elevated levels of D-dimer and C-reactive protein; more high-flow oxygen and invasive mechanical ventilation therapy; higher incidence of acute heart injury, acute respiratory distress syndrome, and deep vein thrombosis; and higher mortality. After a median follow-up period of 51 days, 18 patients died. Compared with survivors, nonsurvivors displayed enlarged right heart chambers, diminished RV function, and elevated pulmonary artery systolic pressure. Male sex, acute respiratory distress syndrome, RVLS, RV fractional area change, and tricuspid annular plane systolic excursion were significant univariate predictors of higher risk for mortality (p < 0.05 for all). A Cox model using RVLS (hazard ratio 1.33; 95% confidence interval [CI] 1.15 to 1.53; p < 0.001; Akaike information criterion = 129; C-index = 0.89) was found to predict higher mortality more accurately than a model with RV fractional area change (Akaike information criterion = 142, C-index = 0.84) and tricuspid annular plane systolic excursion (Akaike information criterion = 144, C-index = 0.83). The best cutoff value of RVLS for prediction of outcome was -23% (AUC 0.87; p < 0.001; sensitivity, 94.4%; specificity, 64.7%). Conclusions: RVLS is a powerful predictor of higher mortality in patients with COVID-19. These results support the application of RVLS to identify higher risk patients with COVID-19.