Construction of containing CT imaging features Nomograms model of postoperative intraluminal thromus formation in patients with aortic dissective aneurysm
10.3760/cma.j.cn115455-20221120-01004
- VernacularTitle:含CT影像特征的主动脉夹层动脉瘤患者术后附壁血栓形成的列线图模型构建
- Author:
Jing LI
1
;
Li TANG
;
Anqiang CHEN
;
Zili YANG
;
Lihua AN
;
Haixia FENG
Author Information
1. 济宁医学院附属医院医学影像科，济宁 272000
- Keywords:
Aortic aneurysm, dissecting;
Stents;
Tomography, spiral computed;
Intraluminal thromus;
Nomograms
- From:
Chinese Journal of Postgraduates of Medicine
2023;46(10):914-920
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the construction of containing CT imaging features Nomograms model of postoperative intraluminal thromus (ILT) formation in patients with aortic dissective aneurysm (ADA).Methods:One hundred and twenty patients with Stanford type B ADA treated with overlapping stent endoluminal repair and multilayer spiral CT (MSCT) examination in Affiliated Hospital of Jining Medical College from May 2020 to February 2022 were selected. The patients were divided into the modeling population (84 patients) and the validation population (36 patients) according to a 7∶3 ratio. The factors influencing postoperative ILT formation in ADA patients were analyzed by univariate and Logistic multifactor regression models, and the prediction model of postoperative ILT formation was constructed based on the influencing factors.Results:In the modeled population, the rate of ILT formation within 1 month after luminal repair with overlapping stents was 27.38%(23/84), including 5 cases in the aortic arch and 18 cases in the abdominal aorta. In the modeled population, the results of univariate analysis showed that the sex, age, body mass index(BMI), smoking, drinking, hypertension, hyperlipidemia, rupture diameter, rupture distance from left subclavicular artery, involvement of important branches, uneven thickening of aneurysm wall, low density on plain scan and operation timing between the ILT formation group and non-ILT formation group had no statistically significant ( P>0.05). The diabetes mellitus, irregular inner wall, calcified plaque, postoperative anticoagulant therapy, B-type brain natriuretic peptide (BNP), fibrinogen (Fib), D-dimer (D-D) and C-reactive protein (CRP) between the two groups had statistical differences: 43.48%(10/23) vs. 11.48%(7/61), 86.96%(20/23) vs. 57.38%(35/61), 91.30%(21/23) vs. 62.30%(38/61), 21.74%(5/23) vs. 57.38%(35/61), (523.60 ± 128.74) ng/L vs.(271.83 ± 109.65) ng/L, (3.82 ± 0.96) g/L vs. (2.85 ± 0.83) g/L, (601.37 ± 75.62) μg/L vs. (389.20 ± 68.79)μg/L, (0.63 ± 0.19) mg/L vs. (0.48 ± 0.15) mg/L, P<0.05. The results of Logistic multifactor regression analysis showed that diabetes mellitus, irregular inner wall, calcified plaque, postoperative anticoagulant therapy and BNP, Fib, D-D CRP levels were influential factors for postoperative ILT formation in Stanford type B ADA patients ( P<0.05). The C-index of the model was 0.903 and 0.894 for the modeled and validated populations, respectively, which had good discrimination and was good at predicting ILT formation after operation in Stanford type B ADA patients. The model had good clinical utility in predicting postoperative ILT formation in Stanford B ADA patients. Conclusions:The Nomograms model can help to screen and identify patients with high risk of ILT formation at an early clinical stage.
