Association Between Insulin Resistance and Incomplete Endothelization of LAAC Devices in Patients with Atrial...

Incomplete endothelialization (IDE) of left atrial appendage closure (LAAC) devices increases the risk of device-related thrombosis (DRT) and stroke. Insulin resistance (IR) may contribute to IDE by impairing endothelial function, but its role remains unclear. This study aimed to investigate the association between IR markers and IDE and develop a predictive model for identifying high-risk patients.

This retrospective observational study included 168 patients with nonvalvular atrial fibrillation (AF) who underwent successful LAAC at Shanghai Ninth People's Hospital between January 2022 and December 2023. IDE was assessed using transesophageal echocardiography (TEE) and cardiac computed tomography angiography (CCTA) at 6 months post-procedure. IR was evaluated using the triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-c) ratio, and metabolic score for insulin resistance (METs-IR). Logistic regression analysis was performed to identify independent predictors of IDE, and a predictive model was constructed.

Among the 168 patients included in the analysis, 43 (25.5%) exhibited IDE, as determined by TEE or CCTA at 6 months post-procedure. Patients with IDE had a significantly higher body mass index, triglyceride (TG) levels, total TG/high-density lipoprotein ratio, TyG index, METs-IR index, and D-dimer levels, as well as a larger maximum LAA orifice diameter (p < 0.05). Multivariate logistic regression identified D-dimer, METs-IR, and maximum LAA orifice diameter as independent predictors of IDE. The predictive probability model incorporating these factors demonstrated high discriminatory ability (area under the curve 0.800, 95% confidence interval 0.71-0.89, p < 0.0001). The optimal predicted probability cut-off value was 0.284, achieving a sensitivity of 76.2% and a specificity of 85.2%.

IR markers, D-dimer levels, and LAA orifice size are significant predictors of IDE following LAAC. The logistic regression model proposed here provides an effective risk stratification tool for identifying patients at higher risk for IDE, enabling personalized anticoagulation strategies and optimizing post-procedural management. Future research should explore whether metabolic interventions can enhance endothelialization and improve long-term outcomes in patients undergoing LAAC.