Abstract Body (Do not enter title and authors here): Background
Mitral annular calcification (MAC) presents significant challenges for the transcatheter edge-to-edge repair (TEER) procedure. However, there are limited data on how the detailed anatomical features of MAC assessed by computed tomography (CT) may be associated with outcomes after TEER. This study aimed to examine the association between CT features of MAC and clinical outcomes after TEER at 3 years.

Methods
This retrospective observational study was conducted at the Cedars-Sinai Medical Center and included patients who underwent TEER and preprocedural CT. Patients were classified into two groups based on the severity of MAC: no/mild MAC and moderate/severe MAC. Classification was determined by scoring calcium thickness, distribution, trigone involvement, and leaflet calcification. The primary outcome was all-cause mortality 3 years after TEER.

Results
Among 391 patients who underwent pre-TEER cardiac CT, 318 (81.3%) had no/mild MAC, and 73 (18.7%) had moderate/severe MAC. No significant differences were noted in all-cause mortality at 3 years between the groups (17.6% vs. 24.7 %; P = 0.17). However, patients with no/mild MAC had significantly better NYHA class than those with moderate/severe MAC at 3 years (P = 0.029). Calcium thickness > 5 mm and leaflet involvement were significant predictors of all-cause mortality at 3 years (OR: 2.38; 95% CI: 1.08–5.25, p=0.032, OR: 6.71; 95% CI: 3.28–13.7, P < 0.001). Subgroup analysis revealed that patients with both significant leaflet calcification and calcium thickness > 5 mm had significantly higher incidences of all-cause mortality compared to those with average calcium thickness ≤ 5 mm and no leaflet calcification.

Conclusions
All-cause mortality did not significantly differ between patients with no/mild MAC and those with moderate/severe MAC. However, greater calcium thickness and leaflet involvement were associated with worse clinical outcomes in patients undergoing TEER. Detailed preoperative CT evaluation can facilitate the prediction and management of TEER outcomes