Abstract 14064: Utility of Tricuspid Annular Plane Systolic Excursion Normalized by Right Ventricular Size in Pulmonary Hypertension to Predict Exercise Capacity, Pulmonary Compliance, and Clinical Outcomes

Abstract

1. Introduction: While tricuspid annular plane systolic excursion (TAPSE) captures the predominant longitudinal motion of right ventricle (RV), it may not accurately predict ventricular function as the RV dilates. Hence, normalizing TAPSE to ventricular area (in systole: TAPSE/RV-area-S, and diastole: TAPSE/RV-area-D) may lead to improved assessment of right heart function. In this study, we aim to determine the utility of RV size-indexed-TAPSE metrics in predicting exercise capacity and clinical outcomes. 2. Methods: We perform a retrospective analysis of 71 consecutive subjects undergoing invasive exercise hemodynamics with cardiopulmonary exercise test for evaluation of dyspnea. Patients were classified into four groups: pulmonary arterial hypertension, isolated post-capillary, combined pre-/post-capillary PH, and control (no PH) based on hemodynamic analysis. Transthoracic echocardiogram data included: TAPSE (mm), TAPSE-index-D (RV end-diastole area in cm), and TAPSE-index-S (RV end-systole area in cm). Subjects were followed for 12 months after hemodynamic study for adverse events (death, heart failure hospitalization). 3. Results: On ROC analysis of indexed-TAPSE to predict pulmonary compliance (>3.0 ml/mmHg), we identified optimal cutoff of 1.1 for TAPSE-index-D (AUC=0.792, p<0.001), 1.5 for TAPSE-index-S (AUC=0.827, p<0.001), and 17 mm for TAPSE (AUC=0.672, p=0.005). Similar results were obtained for predicting %predicted VO 2 max (>50%). We dichotomized indexed-TAPSE based on ROC analysis. As shown in the Figure, compared to the current recommended TAPSE cut-off of 17 mm, RV size-indexed TAPSE metrics were both superior in predicting adverse outcome (p<0.01). 4. Discussion/Conclusion: Normalizing TAPSE to RV size can capture longitudinal and radial motion of the RV as the ventricle dilates and have better ability to predict clinical outcomes (death and HF hospitalization).