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预测 B 型主动脉夹层患者胸主动脉腔内修复术后的不良事件。

Predicting adverse events after thoracic endovascular aortic repair for patients with type B aortic dissection.

机构信息

Department of Peripheral Vascular Diseases, The First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, 710061, Shaanxi, China.

出版信息

Sci Rep. 2024 Apr 5;14(1):8057. doi: 10.1038/s41598-024-58106-7.

Abstract

The potential of adverse events (AEs) after thoracic endovascular aortic repair (TEVAR) in patients with type B aortic dissection (TBAD) has been reported. To avoid the occurrence of AEs, it is important to recognize high-risk population for prevention in advance. The data of 261 patients with TBAD who received TEVAR between June 2017 and June 2021 at our medical center were retrospectively reviewed. After the implementation of exclusion criteria, 172 patients were finally included, and after 2.8 years (range from 1 day to 5.8 years) of follow up, they were divided into AEs (n = 41) and non-AEs (n = 131) groups. We identified the predictors of AEs, and a prediction model was constructed to calculate the specific risk of postoperative AEs at 1, 2, and 3 years, and to stratify patients into high-risk (n = 78) and low-risk (n = 94) group. The prediction model included seven predictors: Age > 75 years, Lower extremity malperfusion (LEM), NT-proBNP > 330 pg/ml, None distal tear, the ratio between the diameter of the ascending aorta and descending aorta (A/D ratio) > 1.2, the ratio of the area of the false lumen to the total aorta (FL ratio) > 64%, and acute TEVAR, which exhibited excellent predictive accuracy performance and discriminatory ability with C statistic of 82.3% (95% CI 77.3-89.2%). The prediction model was contributed to identify high-risk patients of postoperative AEs, which may serve to achievement of personalized treatment and follow-up plans for patients.

摘要

已有研究报道,胸主动脉腔内修复术(TEVAR)治疗 B 型主动脉夹层(TBAD)患者后可能发生不良事件(AEs)。为避免 AEs 的发生,提前识别高危人群并进行预防非常重要。本研究回顾性分析了 2017 年 6 月至 2021 年 6 月在我院接受 TEVAR 治疗的 261 例 TBAD 患者的数据。实施排除标准后,最终纳入 172 例患者,随访 2.8 年(1 天至 5.8 年)后,将其分为 AE(n=41)和非 AE(n=131)组。本研究确定了 AE 的预测因素,并构建了预测模型,以计算术后 1、2 和 3 年的特定 AEs 风险,并将患者分为高危(n=78)和低危(n=94)组。预测模型包括 7 个预测因素:年龄>75 岁、下肢灌注不良(LEM)、NT-proBNP>330pg/ml、无远端撕裂、升主动脉与降主动脉直径比(A/D 比)>1.2、假腔与主动脉总面积比(FL 比)>64%、急性 TEVAR。该预测模型具有出色的预测准确性和区分能力,C 统计量为 82.3%(95%CI:77.3-89.2%)。该预测模型有助于识别术后发生 AEs 的高危患者,从而为患者制定个性化的治疗和随访计划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6483/10997599/bd999e8ecd53/41598_2024_58106_Fig1_HTML.jpg

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