Validation and comparison of prognostic scores for severe tricuspid regurgitation

Abstract Background Severe tricuspid regurgitation (TR) is associated with poor prognosis and significant clinical challenges. Several prognostic risk scores have been developed for this patient population, but they have been poorly externally validated, and their comparative performance remains largely unexplored. Objectives This study aimed to validate and compare the performance of established prognostic risk scores in a real-world cohort of patients with severe TR. Methods We retrospectively analyzed 476 patients with severe TR treated at our institution between 2018 and 2023. Patients were categorized into three groups based on their treatment strategy: conservative management (n=323), tricuspid valve surgery (n=76), and transcatheter tricuspid edge-to-edge repair (n=77). We evaluated five prognostic risk scores (TRI-SCORE, Wang score, TRIVALVE, Hochstadt score, and TRIO score) using area under the curve (AUC) analyses for all-cause mortality and the composite endpoint (all-cause mortality or heart failure hospitalization) at two years of follow-up. Results Among the evaluated scores, the TRI-SCORE consistently demonstrated the highest accuracy across all treatment strategies and endpoints. In the overall cohort, the TRI-SCORE achieved an AUC of 0.71 (95% CI: 0.65–0.76) for all-cause mortality and 0.68 (95% CI: 0.63–0.73) for the composite endpoint. Notably, the TRI-SCORE showed particularly strong performance in surgically managed patients, with an AUC of 0.86 (95% CI: 0.75–0.96) for mortality. Conclusions This study represents the first external validation of all currently published prognostic risk scores for severe TR within a real-world cohort. The TRI-SCORE demonstrated the highest predictive accuracy, particularly in patients undergoing surgical intervention, reinforcing its utility in guiding clinical decision-making. Its simplicity and feasibility further enhance its applicability in routine clinical practice.Comparative ValidationFor image description, please refer to the figure legend and surrounding text.