Abstract 11419: Combination of Right Ventricular Global Longitudinal Strain and Conventional Echocardiographic Parameter Carries Improved Prognostic Value in Submassive Pulmonary Embolism

Abstract

Introduction and Hypothesis: Right ventricular (RV) dysfunction has been identified as a prognostic marker for adverse clinical events in patients with submassive pulmonary embolism (PE). We hypothesized that combination of right-sided strain analysis and conventional parameters can further risk stratify patients at high risk for mortality. Methods: Retrospective cohort study of patients with submassive PE between 2010 and 2018. The primary outcome was all-cause mortality at 30 days. Echocardiographic parameters including right to left ventricular end-diastolic diameter ratio (RV/LV ratio), RV global longitudinal strain (RVGLS), RV free wall strain and right atrium strain were compared between survivors and non-survivors. Multivariable analysis and receiver operator characteristic (ROC) curves analysis were used to demonstrate the predictive value of baseline measurements. Results: 251 patients were analyzed. Overall mortality rate at 30 days was 12.4 %. Multivariable analysis revealed RV/LV ratio was an independent predictor of 30-day mortality in conventional parameters, and RVGLS was also an independent predictor among the three strain parameters. ROC curves indicated that the best cutoff values for RVGLS and RV/LV ratio to predict mortality were 17.7 % and 1.03. When the 230 patients with measurable RVGLS and RV/LV ratio were divided into four groups using both cutoff values, patients with both high RVGLS and low RV/LV ratio had the lowest mortality (1.0 % at 30 days; n = 99) while patients with both low RVGLS and high RV/LV ratio had the highest mortality (46.2 % at 30 days; n = 39). Kaplan-Meier curves depicted the significantly different prognosis among the four groups (p < 0.001. Figure). Conclusions: The combination of RVGLS and RV/LV ratio can help further risk stratify patients with submassive PE. This may identify patients at highest risk of mortality and ultimately alter treatment pathways.