A novel echocardiography-based definition of atrial functional tricuspid regurgitation (A-FTR) has shown superior outcomes in patients undergoing conservative treatment or tricuspid valve transcatheter edge-to-edge repair. Its prognostic significance for transcatheter tricuspid valve annuloplasty (TTVA) outcomes is unknown. This study sought to investigate prognostic, clinical, and technical implications of A-FTR phenotype in patients undergoing TTVA. This multicenter study investigated clinical and echocardiographic outcomes up to 1 year in 165 consecutive patients who underwent TTVA for A-FTR (characterized by the absence of tricuspid valve tenting, midventricular right ventricular [RV] dilatation, and impaired left ventricular ejection fraction) and nonatrial functional tricuspid regurgitation (NA-FTR). A total of 62 A-FTR and 103 NA-FTR patients were identified, with the latter exhibiting more pronounced RV remodeling. Compared to baseline, the tricuspid regurgitation (TR) grade at discharge was significantly reduced (P < 0.001 for both subtypes), and TR ≤II was achieved more frequently in A-FTR (85.2% vs 60.8%; P = 0.001). Baseline TR grade and A-FTR phenotype were independently associated with TR ≤II at discharge and 30 days. In multivariate analyses, A-FTR phenotype was a strong predictor (OR: 5.8; 95% CI: 2.1-16.1; P < 0.001) of TR ≤II at 30 days. At 1 year, functional class had significantly improved compared to baseline (both P < 0.001). One-year mortality was lower in A-FTR (6.5% vs 23.8%; P = 0.011) without significant differences in heart failure hospitalizations (13.3% vs 22.7%; P = 0.188). Direct TTVA effectively reduces TR in both A-FTR, which is a strong and independent predictor of achieving TR ≤II, and NA-FTR. Even though NA-FTR showed more RV remodeling at baseline, both phenotypes experienced similar symptomatic improvement, emphasizing the benefit of TTVA even in advanced disease stages. Additionally, phenotyping was of prognostic relevance in patients undergoing TTVA.

The GLIDE Score is an anatomical scoring system designed to predict moderate residual tricuspid regurgitation (TR) immediately following transcatheter tricuspid edge-to-edge repair (T-TEER). The purpose of this study was to evaluate the GLIDE Score's predictive capability for achieving a postprocedural TR grade of mild or better. This retrospective analysis included 336 patients from a multicenter registry who underwent T-TEER between January 2017 and November 2022. Anatomical features were assessed using transesophageal echocardiography to calculate the GLIDE Score, which ranges from 0 to 5. The primary endpoint was a postprocedural TR grade of mild or better, assessed via periprocedural imaging. Outcomes were compared between patients with GLIDE Scores of 0 to 1 and those with scores ≥2 using logistic regression and ROC curve analysis. Median age was 81 years, with no significant differences in BMI, EuroScore II, or NYHA Class across GLIDE Score cohorts. The GLIDE Score ≥2 cohort had a larger median RV basal diameter (48 mm vs 45 mm, P < 0.001) and more torrential TR cases (35.9% vs 3.1%, P < 0.001). Postprocedural mild TR was achieved in 74.7% of patients with a GLIDE Score of 0 to 1, versus 13.4% in the ≥2 cohort (P < 0.001). Ordinal regression analysis found a strong correlation between the GLIDE Score and postprocedural TR severity (coefficient = 1.41, t = 12.92), with an AUC to predict mild TR of 0.87 (95% CI: 0.83-0.90). The GLIDE Score is a valuable tool for predicting postprocedural TR severity in T-TEER patients, guiding patient selection and refining treatment strategies.

Baseline right ventricular (RV) function derived from 3-dimensional analyses has been demonstrated to be predictive in patients undergoing transcatheter tricuspid valve repair (TTVR). The complex nature of these cumbersome analyses makes patient selection based on established imaging methods challenging. Artificial intelligence (AI)-driven computed tomography (CT) segmentation of the RV might serve as a fast and predictive tool for evaluating patients prior to TTVR. Patients suffering from severe tricuspid regurgitation underwent full cycle cardiac CT. AI-driven analyses were compared to conventional CT analyses. Outcome measures were correlated with survival free of rehospitalization for heart-failure or death after TTVR as the primary endpoint. Automated AI-based image CT-analysis from 100 patients (mean age 77 ± 8 years, 63% female) showed excellent correlation for chamber quantification compared to conventional, core-lab evaluated CT analysis (R 0.963-0.966; p < 0.001). At 1 year (mean follow-up 229 ± 134 days) the primary endpoint occurred significantly more frequently in patients with reduced RV ejection fraction (EF) 210 ml and RV EF <50% demonstrated worse outcome than patients with functional RVs (43.7% vs. 12.2%; HR 3.753, CI 1.621-8.693; p = 0.002). Derived RVEF and dysfunctional RV were predictors for death and hospitalization after TTVR. AI-facilitated CT analysis serves as an inter- and intra-observer independent and time-effective tool which may thus aid in optimizing patient selection prior to TTVR in clinical routine and in trials.