ObjectiveThis paper aimed to summarize the new progress in surgical indications regarding as maximum diameter from evidence-based medical evidence and morphological rupture-risk assessment of abdominal aortic aneurysms (AAA) and its clinical application value.MethodThe rupture-risk and its mechanism of AAA in specific population and morphological characteristics were reviewed.ResultsAsymptomatic patients in specific subgroups may also benefit from AAA repair by lowering the intervention threshold. Besides the maximum diameter of aneurysm, other morphological factors, such as the true geometric shape, the wall thickness, and mural thrombus also had important predictive value for AAA rupture risk.ConclusionRupture-risk assessment based on the actual individual situation of AAA patients can further facilitate the clinical diagnosis and treatment.
Objective To explore the application model and value of artificial intelligence (AI) in interventional vascular surgery education. MethodsSupported by AI technologies, a teaching framework was established from three dimensions: personalized learning and assessment, surgical operation training, interdisciplinary collaboration, and lifelong learning. Combined with clinical cases, the teaching process was refined, use quantitative assessment and multimodal simulation training to achieve personalized teaching and clinical skills improvement. ResultsLearners’ data profiles can be generate by AI through dynamic capability evaluation, accurately deliver multimodal resources, and optimize personalized assessment. With VR/AR simulation and staged training, learners’ operation accuracy, hand stability, and complication management ability can be improved. The virtual multidisciplinary platform and intelligent literature recommendation enhanced interdisciplinary collaboration and knowledge updating. This model can improve teaching efficiency and assessment objectivity, yet faced challenges including data dependence, insufficient algorithm interpretability, and high cost. ConclusionsAI provides a personalized, precise, and standardized pathway for interventional vascular surgery education, effectively elevating teaching quality and clinical skills. Further efforts are needed to perfect data standards, optimize algorithms, and strengthen security specification to promote the safe and effective application of AI in medical education.
Objective To investigate the influencing factors for restenosis after femoral endarterectomy in treatment of arteriosclerosis obliterans at femoral artery . Methods A total of 103 patients with arteriosclerosis obliterans at femoral artery who underwent femoral endarterectomy from Jan. 2012 to Jan. 2017 in our hospital were retrospectively selected as subjects of this study, to compare the clinical feathers between restenosis group and patent group, and then exploring the influencing factors for restenosis after femoral endarterectomy. Results Thirty-six patients (35.0%) suffered from restenosis after femoral endarterectomy. Patients in the restenosis group had a high proportion of high smoking and diabetes mellitus, and high level of low density lipoprotein than those corresponding indexes of the patent group (P<0.05). Results of Cox proportional hazard model showed that, diabetes mellitus 〔RR=3.338, 95% CI was (1.003, 11.113), P=0.049〕 and high level of low density lipoprotein 〔RR=3.311, 95% CI was (1.166, 9.397), P=0.024〕 were independent risk factors for restenosis after femoral endarterectomy. Conclusions Monitoring of high-risk factors like controlling blood glucose strictly and strengthening statin treatment should be done to reduce the risk of restenosis after femoral endarterectomy for patients with arteriosclerosis obliterans at femoral artery.