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经导管主动脉瓣置换术后的脑血管事件:预测不可预测情况的困难

Cerebrovascular Events after Transcatheter Aortic Valve Replacement: The Difficulty in Predicting the Unpredictable.

作者信息

Maier Oliver, Bosbach Georg, Piayda Kerstin, Afzal Shazia, Polzin Amin, Westenfeld Ralf, Jung Christian, Kelm Malte, Zeus Tobias, Veulemans Verena

机构信息

Department of Cardiology, Pulmonology and Vascular Medicine, Medical Faculty, Heinrich Heine University, 40225 Duesseldorf, Germany.

CardioVascular Center (CVC) Frankfurt, 60389 Frankfurt, Germany.

出版信息

J Clin Med. 2022 Jul 4;11(13):3902. doi: 10.3390/jcm11133902.

Abstract

Background: Cerebrovascular events (CVE) are feared complications following transcatheter aortic valve replacement (TAVR). We aimed to develop a new risk model for CVE prediction with the application of multimodal imaging. Methods: From May 2011 to August 2019, a total of 2015 patients underwent TAVR at our institution. The study cohort was subdivided into a derivation cohort (n = 1365) and a validation cohort (n = 650) for risk model development. Results: Of 2015 patients, 72 (3.6%) developed TAVR-related CVE. Pre-procedural factors of our risk model were history of prior CVE, a larger aortic valve area (≥0.55 cm2), a large aortic angulation (≥48.5°), and enhanced calcification of the right coronary cusp (≥447.2 AU), left ventricular outflow tract (≥262.4 AU), and ascending thoracic aorta (≥116.4 AU). Our risk model was superior for in-hospital CVE prediction following TAVR in the establishment cohort (AUC 0.73, 95% CI 0.66−0.80; p < 0.001) compared to other risk scores, such as the EuroSCORE II or the CHA2DS2-VASc score. Conclusions: Although CVE prediction in patients undergoing TAVR is challenging due to the complex nature of the TAVR procedure, our study highlights that multimodal imaging is a promising approach to generate a more accurate risk model for CVE prediction.

摘要

背景

脑血管事件(CVE)是经导管主动脉瓣置换术(TAVR)后令人担忧的并发症。我们旨在应用多模态成像技术开发一种新的CVE预测风险模型。方法:2011年5月至2019年8月,共有2015例患者在我院接受了TAVR治疗。为了开发风险模型,研究队列被细分为一个推导队列(n = 1365)和一个验证队列(n = 650)。结果:在2015例患者中,72例(3.6%)发生了与TAVR相关的CVE。我们风险模型的术前因素包括既往CVE病史、较大的主动脉瓣面积(≥0.55 cm²)、较大的主动脉夹角(≥48.5°)以及右冠状动脉瓣叶(≥447.2 AU)、左心室流出道(≥262.4 AU)和升主动脉(≥116.4 AU)的钙化增强。与其他风险评分(如欧洲心脏手术风险评估系统II(EuroSCORE II)或CHA2DS2-VASc评分)相比,我们的风险模型在建立队列中对TAVR术后院内CVE预测方面更具优势(AUC 0.73,95%CI 0.66−0.80;p < 0.001)。结论:尽管由于TAVR手术的复杂性,对接受TAVR治疗的患者进行CVE预测具有挑战性,但我们的研究强调多模态成像是生成更准确的CVE预测风险模型的一种有前景的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fb1/9267500/9a1b226ae57c/jcm-11-03902-g001.jpg

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