Objective: To identify the risk factors associated with moderate to severe perivalvular leakage (PVL) after transcatheter aortic valve replacement (TAVR) and to construct a prediction model for this risk.
Methods: A retrospective analysis was conducted on 128 patients with severe aortic stenosis who had received TAVR in The Second Hospital of Hebei Medical University from January 2019 to January 2024. The length of the aortic regurgitation bundle and annular circumference ratio were measured by transesophageal echocardiography immediately after the valve implantation. Patients with moderate to severe PVL were included in observation group, while the remaining comprised the control group. Clinical data of the patients were recorded, and univariate and multivariate Logistic regression analyses were performed on factors potentially influencing the development of moderate to severe PVL after surgery. A risk prediction model was constructed correspondingly.
Results: Of the 128 patients, 51 with moderate or severe PVL served as the observation group and the remaining 77 served as the control group. The results of univariate and multivariate analyses identified LVOT coverage index, depth of valve implantation, LVEDd, aortic angulation, LVESD, and calcification volume entered as independent risk factors associated with moderate to severe PVL following TAVR (P<0.05). A predictive model for post-TAVR PVL was constructed by incorporating these significant factors. ROC curve analysis of the prediction model for moderate to severe PVL showed an area under the curve of 0.911.
Conclusion: LVOT coverage index, depth of valve implantation, LVEDd, aortic angulation, LVESD, and calcification volume are independent risk factors for moderate to severe PVL in patients with severe aortic stenosis after TAVR. Risk prediction model constructed based on the risk factors are valuable tool for identifying patients at high risk of developing moderate or greater PVL post-surgery.
Keywords: Transcatheter aortic valve replacement; perivalvular leakage; postoperative complications; prediction model; risk factors.
AJTR Copyright © 2024.