Kane, GC

Abstract Funding Acknowledgements Type of funding sources: None. Background Pulmonary hypertension (PH) is a progressive pulmonary vascular disorder with an elevated mortality risk due to right ventricular failure. Pulmonary arterial pulsatility index (PAPi) based on invasively acquired parameters has emerged as a potentially valuable hemodynamic risk predictor. Whether non-invasively derived PAPi (PA pulse pressure/ RA pressure) is valuable is unclear. Purpose To assess whether PAPi measured non-invasively by transthoracic echocardiography acts as a prognostic hemodynamic biomarker of patient risk. Methods Consecutive patients undergoing transthoracic echocardiography for known or suspected PH over a one year period were included. PA systolic and diastolic pressure were estimated in standard fashion from peak tricuspid and end-pulmonary regurgitant Doppler profiles. Right atrial pressure was estimated based on 2D & Doppler assessment of the inferior vena cava hepatic vein. In those patients with PH (mean PA pressure > 20 mm Hg), PAPi was divided into 3 groups based on prior publications with invasive data as <1.5, 1.5 to 3 and >3. Mortality was assessed over 5 years. Results Of 1,045 patients enrolled 64% had PH. Patients with the lowest PAPi (table) had higher NT-proBNP levels, larger right ventricles, worse right heart systolic function (cardiac output, TAPSE, systolic annular velocity, free wall systolic strain) and greater degrees of tricuspid regurgitation (Table). In patients with PH, PAPi was inversely associated with death (figure, p < 0.0001) with each group of PAPi correlating with incrementally worse survival. Patients with a PAPi of <1.5 had worst right heart size and dysfunction on echo (table) and worst survival (figure). Conclusions In patients with PH, low PAPi derived non-invasively by transthoracic echocardiography is associated with markers of right heart failure, right ventricular dysfunction and worse survival. PAPi could be incorporated into the conventional echo parameters reported in patients with known or suspected PH and maybe a useful predictor of outcome. Abstract Table Abstract Figure

Abstract Funding Acknowledgements Type of funding sources: None. Background Tricuspid regurgitation (TR) is a prevalent valvular lesion with three broad morphologic subtypes: primary due to intrinsic pathology of the valve or subvalvular apparatus; secondary due to pulmonary hypertension; and isolated TR associated with chronic atrial fibrillation. The complex pathophysiological, clinical and echocardiographic features between these subtypes require further investigation. Purpose We aimed to identify the different phenotypes of TR using cluster analysis, and determine differences (if present) in clinical outcomes associated with these phenotypes. Methods We included 13611 patients with ≥ moderate TR, either primary or secondary, in the final analyses. The demographic, clinical and echocardiographic data of these patients were evaluated using Ward’s minimum variance cluster analysis including a total of 38 variables. Survival analysis for all-cause mortality was performed using the Kaplan-Meier method, and groups were compared using the log-rank test. Results The mean age of patients was 72.5 ± 13.4 years, 7590 (56%) were females. The clustering identified 5 distinct phenotypes. Cluster 1 represented "low-risk TR" with lesser severity likely related to chronic atrial fibrillation. This cluster had less severe TR, normal sized right ventricle and fewer comorbidities. Clusters 2-5 represented "higher severity TR", "TR associated with lung disease", "TR associated with coronary artery disease and ischemic cardiomyopathy" and "TR associated with chronic kidney disease" respectively (Figure 1). Cluster 1 had the best overall survival, followed by clusters 2, 3 and 4, and lastly cluster 5, with the worst outcome (Figure 2). Conclusions Cluster analysis identifies 5 phenotypically distinct novel subgroups of TR with differences in all-cause mortality. This phenotype-based classification improves our understanding of interaction of different co-morbidities with this complex valve lesion and can inform clinical decision making. Abstract Figure. Cluster Dendrogram Abstract Figure. Kaplan-Meier survival curves