ArticleScientific reports2024
Predicting adverse events after thoracic endovascular aortic repair for patients with type B aortic dissection.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
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.
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