ArticleScientific reports2024
Risk prediction and prognostic analysis of post-implantation syndrome after thoracic endovascular aortic repair.
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 5 papers.
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Who cites it
5 citing papers in PubMed.
- Preoperative exercise tolerance, nutritional-inflammatory markers, and outcomes after TEVAR for type B aortic pathology.Frontiers in cardiovascular medicine · 2026Article
- Thrombo-inflammation as a missing variable in thoracic aortic intervention timing: toward a biology-informed threshold.Frontiers in cardiovascular medicine · 2026Review
- Postimplantation syndrome following stentless thoracic endovascular aortic repair of chronic aortic dissection.Journal of vascular surgery cases and innovative techniques · 2025Article
- Evaluation of perivascular fat density and residual false lumen formation following TEVAR in Stanford type B aortic dissection.Frontiers in cardiovascular medicine · 2025Article
- Stent-Induced Inflammation: A Comparative Cross-Sectional Study of Post-Implantation Syndrome in Venous and Arterial Procedures.Journal of clinical medicine · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
This study aimed to establish a predictive model for the risk of post-thoracic endovascular aortic repair (TEVAR) post-implantation syndrome (PIS) in type B aortic dissection (TBAD) patients, assisting clinical physicians in early risk stratification and decision management for high-risk PIS patients. This study retrospectively analyzed the clinical data of 547 consecutive TBAD patients who underwent TEVAR treatment at our hospital. Feature variables were selected through LASSO regression and logistic regression analysis to construct a nomogram predictive model, and the model's performance was evaluated. The optimal cutoff value for the PIS risk nomogram score was calculated through receiver operating characteristic (ROC) curve analysis, further dividing patients into high-risk group (HRG) and low-risk group (LRG), and comparing the short to midterm postoperative outcomes between the two groups. In the end, a total of 158 cases (28.9%) experienced PIS. Through LASSO regression analysis and multivariable logistic regression analysis, variables including age, emergency surgery, operative time, contrast medium volume, and number of main prosthesis stents were selected to construct the nomogram predictive model. The model achieved an area under the curve (AUC) of 0.86 in the training set and 0.82 in the test set. Results from calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) demonstrated that the predictive model exhibited good performance and clinical utility. Furthermore, after comparing the postoperative outcomes of HRG and LRG patients, we found that the incidence of postoperative PIS significantly increased in HRG patients. The duration of ICU stay and mechanical assistance time was prolonged, and the incidence of postoperative type II entry flow and acute kidney injury (AKI) was higher. The risk of aortic-related adverse events (ARAEs) and major adverse events (MAEs) at the first and twelfth months of follow-up also significantly increased. However, there was no significant difference in the mortality rate during hospitalization. This study established a nomogram model for predicting the risk of PIS in patients with TBAD undergoing TEVAR. It serves as a practical tool to assist clinicians in early risk stratification and decision-making management for patients.
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