Association between pre-procedural computed tomography angiography-based global longitudinal strain and outcomes in patients undergoing transcatheter aortic valve implantation

术前计算机断层扫描血管造影测得的整体纵向应变与经导管主动脉瓣置换术患者预后的关系

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Abstract

BACKGROUND: Computed tomography angiography-based global longitudinal strain (CTA-GLS) is feasible for myocardial assessment, but limited data are available for patients undergoing transcatheter aortic valve implantation (TAVI). This study sought to analyze the association between CTA-GLS and perioperative aortic regurgitation (AR), and its prognostic value in TAVI patients. METHODS: Consecutive TAVI recipients at Beijing Anzhen Hospital were enrolled in this retrospective study from June 2021 to January 2024. The patients underwent transthoracic echocardiography (TTE), and pre-TAVI CTA. Nonlinear relationships between CTA-GLS and AR were evaluated using restricted cubic splines (RCSs). The performance of the multivariate Cox proportional hazards models were assessed by the concordance index (C-index), integrated discrimination improvement (IDI), and net reclassification improvement (NRI). RESULTS: The study included 369 TAVI patients with a median age of 73.0 years, of whom 56.1% were male. CTA-GLS exhibited a strong nonlinear correlation with pre-procedural AR (P<0.001) and post-operative AR improvement (P=0.004). In the multivariate Cox proportional hazards regression, each 1% absolute decrease in CTA-GLS remained a significant predictor of all-cause mortality and heart failure hospitalization (HFH) post-TAVI [hazard ratio (HR): 1.47; 95% confidence interval (CI): 1.22-1.78; P<0.001]. The following three nested models were developed: Model 1, which included clinical parameters; Model 2, which included CTA-GLS, and Model 3, which combined both. Adding CTA-GLS improved the C-index from 0.66 (95% CI: 0.53-0.79) to 0.81 (95% CI: 0.75-0.87) (P=0.028), which was also reflected in the NRI [0.89 (95% CI: 0.56-1.22), P<0.001] and IDI [0.05 (95% CI: 0.02-0.09), P=0.003]. CONCLUSIONS: Pre-TAVI CTA-GLS is nonlinearly linked to pre-procedural AR and its improvement. It can be used to independently predict post-TAVI outcomes and adds incremental value to clinical parameters.

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