Objective:To establish the predictive model for major adverse cardiovascular events(MACE) following endovascular repair in elderly patients with abdominal aortic aneurysm(AAA).Methods:The clinical data and postoperative MACE were retrospectively collected from elderly patients with AAA who underwent their first endovascular aneurysm repair(EVAR)in Beijing Hospital and Tibet Autonomous Region People's Hospital between January 2016 and December 2023.Patients were randomly divided into training and validation cohorts at a ratio of 7∶3.Predictive models were using logistic regression, LASSO regression, random forest, linear discriminant analysis, na?ve Bayes, k-nearest neighbor algorithm, support vector machine, decision tree, and AdaBoost.Models were evaluated using receiver operating characteristic(ROC)curves.Results:A total of 171 elderly AAA patients were enrolled, aged 60 to 94 years(mean 73.0 ± 7.5 years), of whom 145 were male.MACE occurred after EVAR in 30 patients(17.5%). LASSO regression identified monocyte count, history of coronary artery disease, the ratio of maximum AAA diameter to body mass index(DBR), neutrophil-lymphocyte count ratio(NLR), and age as significant predictors, yielding an area under the ROC curve(AUC)of 0.816.Logistic regression achieved an AUC of 0.813 in the training cohort and 0.772 in the validation cohort.Among all models, AdaBoost demonstrated the best performance, with an AUC of 0.92 in the validation cohort.Conclusions:Age, monocyte count, DBR, NLR and creatinine could predict the occurrence of MACE after EVAR in AAA patients.The AdaBoost model provides the most accurate prediction of postoperative MACE.

Objective:To establish the predictive model for major adverse cardiovascular events(MACE) following endovascular repair in elderly patients with abdominal aortic aneurysm(AAA).Methods:The clinical data and postoperative MACE were retrospectively collected from elderly patients with AAA who underwent their first endovascular aneurysm repair(EVAR)in Beijing Hospital and Tibet Autonomous Region People's Hospital between January 2016 and December 2023.Patients were randomly divided into training and validation cohorts at a ratio of 7∶3.Predictive models were using logistic regression, LASSO regression, random forest, linear discriminant analysis, na?ve Bayes, k-nearest neighbor algorithm, support vector machine, decision tree, and AdaBoost.Models were evaluated using receiver operating characteristic(ROC)curves.Results:A total of 171 elderly AAA patients were enrolled, aged 60 to 94 years(mean 73.0 ± 7.5 years), of whom 145 were male.MACE occurred after EVAR in 30 patients(17.5%). LASSO regression identified monocyte count, history of coronary artery disease, the ratio of maximum AAA diameter to body mass index(DBR), neutrophil-lymphocyte count ratio(NLR), and age as significant predictors, yielding an area under the ROC curve(AUC)of 0.816.Logistic regression achieved an AUC of 0.813 in the training cohort and 0.772 in the validation cohort.Among all models, AdaBoost demonstrated the best performance, with an AUC of 0.92 in the validation cohort.Conclusions:Age, monocyte count, DBR, NLR and creatinine could predict the occurrence of MACE after EVAR in AAA patients.The AdaBoost model provides the most accurate prediction of postoperative MACE.

Peripheral arterial disease (PAD) is associated with a high risk of mortality and amputation. However,many PAD patients remain asymptomatic or present with atypical symptoms,leading to low awareness and diagnostic rates. With an aging population and the increasing prevalence of risk factors,the burden of PAD is expected to grow. Artificial intelligence (AI),encompassing machine learning,deep learning,natural language processing,and computer vision,refers to machines and algorithms capable of simulating human intelligence and performing human-like tasks. Although the application of AI in PAD is still in its early stages,its potential is substantial. This article reviews the current clinical applications and limitations of AI in the management of PAD patients.

Peripheral arterial disease (PAD) is associated with a high risk of mortality and amputation. However,many PAD patients remain asymptomatic or present with atypical symptoms,leading to low awareness and diagnostic rates. With an aging population and the increasing prevalence of risk factors,the burden of PAD is expected to grow. Artificial intelligence (AI),encompassing machine learning,deep learning,natural language processing,and computer vision,refers to machines and algorithms capable of simulating human intelligence and performing human-like tasks. Although the application of AI in PAD is still in its early stages,its potential is substantial. This article reviews the current clinical applications and limitations of AI in the management of PAD patients.

Objective:To evaluate the effect of remote endarterectomy in the treatment of complex lower extremity ischemia.Methods:Twenty-one limb ischemic patients underwent remote endarterectomy in Beijing Hospital from Sep 2016 to Feb 2020. Clinical data including general condition, the lesion of lower artery before operation and follow up outcomes were collected. Then the patency rate and limb salvage rate were calculated.Results:The technique success rate was 71.4% (15/21). The 3, 6, 12 month patency rate were 93.3%, 85.6% and 74.1%, respectively. The 1-year limb salvage rate was 93.3% (14/15). In the 6 patients converted to artificial vessel bypass, the 3,6,12 months patency rates were 76.7%, 66.7% and 46.8%, respectively. The 1-year limb salvage rate was 66.7%.Conclusions:Remote endarterectomy of the lower extremity artery is an alternative option in the treatment of complex ischemic lesions of the lower extremity artery, other than artificial vessel bypass.

Objective:To analyze the relevant risk factors for restenosis after percutaneous transluminal angioplasty of patients with Takayasu′s arteritis.Methods:Clinical data of 43 patients undergoing percutaneous angioplasty due to Takayasu arteritis were retrospectively analyzed. Univariate and multivariate Logistic regression analysis was used to explore the relevant risk factors for restenosis after percutaneous transluminal angioplasty.Results:There were 9 males and 34 females. The mean age was 23 (18-33) years old, 59 times of PTA were performed, including 44 in renal artery, 9 in aorta, 2 in iliac and 2 in carotid artery, 1 in brachiocephalic trunk and 1 in left subclavian artery. The mean follow up time was (64±42) months. The rate of restenosis was 47.5%(28/59)and the mean time of restenosis was (23±27) months. The restenosis rate of aorta and iliac artery was 9.1%, that of renal artery was 52.3% and that of supra aortic artery was 100% . The rate of restenosis was higher in patients with symptoms of headache, syncope and low back pain, the elevated ESR and CRP increased the risk of restenosis (all P<0.05). Multivariate Logistic analysis showed that preoperative elevation of ESR and CRP were risk factors for restenosis after percutaneous angioplasty for Takayasu arteritis. Conclusions:PTA was safe and effective in Takayasu arteritis involving aorta-iliac and renal artery, the elevated ESR and CRP was related to high risk of restenosis.

Objective To analyze the risk factors of restenosis after renal artery endovascular treatment in patients with Takayasu arteritis.Methods In this study,39 patients with Takayasu arteritis underwent endovascular therapy from January 2003 to March 2014.Univariate and multivariate logistic regression analysis were used to analyze the risk factors relating to restenosis.Results There were 13 males and 26 females.The mean age was (27 ± 11) years.Seventeen unilateral and 22 bilateral renal artery stenosis were treated.A total of 54 endovascular procedures were successfully performed including 23 cases of unilateral percutaneous transluminal angioplasty (PTA),14 cases of unilateral stent implantation,12 cases of bilateral PTA,and 5 cases of bilateral stent implantation.The mean follow-up was (48 ±34) months,the restenosis rate was 38.9％ (21.54) and the mean time of restenosis was (11.5 ± 2.3) months.Elevated erythrocyte sedimentation rate (ESR) (OR =6.624,95 ％ CI:1.222-35.902) was independent risk factors for restenosis.Antiplatelet therapy (OR =0.158,95％ CI:0.028-0.887) and glucocorticoids or i mmunosuppressive therapy (OR =0.035,95 ％ CI:0.003-0.349) were protection factors against renal artery restenosis.Conclusion The elevated ESR increases the risk of restenosis after endovascular treatment in Takayasu arteritis associated renal artery stenosis.Antiplatelet therapy and glucocorticoids or immunosuppressive therapy were protection factors for renal artery restenosis.

Objective To evaluate the technical success,adverse events in 30 days after endovascular repair for acute and non-acute Stanford B aortic dissection.Methods A search was performed to identify all Chinese literatures that compare the effect of TEVAR on acute and non-acute Stanford B dissection in WanFang and Chinese National Knowledge Infrastructure (CNKI) from 2009 to 2014.Literatures were extracted and x2 test conducted by SPSS 17.0 software,REVMAN 5.3 software was used to conduct meta-analysis and bias analysis by STATA software.Results 5 studies including 468 patients (acute group 243,non-acute group 225) were extracted.Acute Stanford B dissection have higher rate both in total complications(OR =3.10,95％ CI =[1.74,5.53],P =0.0001) and endoleaks (OR =2.07,95％ CI =[1.11,3.88],P =0.02) within 30 days than non-acute group,the technique success rate (P =0.3),the mortality rate within 30 days (P =0.27) as well as aortic related mortality rate (P =0.26)show no significant difference.Conclusion Acute Stanford B dissection have higher rate of total postoperative complications,endoleaks within 30 days than non-acute group,with similar surgical success rate,30 days mortality rate and aorta related mortality rate.