Objective:To investigate the safety and efficacy of Pipeline embolization device (PED) Shield in intracranial unruptured saccular aneurysms.Methods:This is a retrospective cohort study; 124 patients with intracranial unruptured saccular aneurysms treated with PED Shield at Department of Cerebrovascular Surgery, Neurosurgery Center, Zhujiang Hospital, Southern Medical University from July 2023 to October 2024 were enrolled. Intraoperative device-related complications and occurrence of hemorrhagic and ischemic complications within 30 days of the procedure were recorded. The clinical results and imaging results (degrees of stent patency and aneurysm occlusion rate) 6 months after follow-up were statistically analyzed. Modified Rankin scale (mRS) score>2 was defined as poor prognosis in clinical follow-up, and grade D according to O'Kelly Marotta (OKM) classification was considered as complete aneurysm occlusion in imaging follow-up.Results:Eighty-seven females and 37 males, aged (56.44±12.17) years (ranging from 27 to 80 years) were enrolled, with a maximum aneurysm diameter of 5.12 (3.73, 7.24) mm. Among the 124 patients, incidence of intraoperative instrument-related complications was 6.5% (8/124); and within 30 days of the procedure, incidence of ischemic complications was 4.8% (6/124) and that of hemorrhagic complications was 1.6% (2/124). Eighty-four patients had a 6-month clinical follow-up, with 1 patient (1.2%) having poor prognosis. Eighty-four patients (67.7%) completed a 6-month imaging follow-up: complete occlusion rate of aneurysms was 82.1% (69/84), incidence of in-stent stenosis (stenosis degree ≥25%) was 4.8% (4/84), and no symptomatic in-stent stenosis was found.Conclusion:Result of this study shows that PED Shield may be an effective and safe clinical option for intracranial unruptured saccular aneurysms.

Objective:To investigate the safety and efficacy of Pipeline embolization device (PED) Shield in intracranial unruptured saccular aneurysms.Methods:This is a retrospective cohort study; 124 patients with intracranial unruptured saccular aneurysms treated with PED Shield at Department of Cerebrovascular Surgery, Neurosurgery Center, Zhujiang Hospital, Southern Medical University from July 2023 to October 2024 were enrolled. Intraoperative device-related complications and occurrence of hemorrhagic and ischemic complications within 30 days of the procedure were recorded. The clinical results and imaging results (degrees of stent patency and aneurysm occlusion rate) 6 months after follow-up were statistically analyzed. Modified Rankin scale (mRS) score>2 was defined as poor prognosis in clinical follow-up, and grade D according to O'Kelly Marotta (OKM) classification was considered as complete aneurysm occlusion in imaging follow-up.Results:Eighty-seven females and 37 males, aged (56.44±12.17) years (ranging from 27 to 80 years) were enrolled, with a maximum aneurysm diameter of 5.12 (3.73, 7.24) mm. Among the 124 patients, incidence of intraoperative instrument-related complications was 6.5% (8/124); and within 30 days of the procedure, incidence of ischemic complications was 4.8% (6/124) and that of hemorrhagic complications was 1.6% (2/124). Eighty-four patients had a 6-month clinical follow-up, with 1 patient (1.2%) having poor prognosis. Eighty-four patients (67.7%) completed a 6-month imaging follow-up: complete occlusion rate of aneurysms was 82.1% (69/84), incidence of in-stent stenosis (stenosis degree ≥25%) was 4.8% (4/84), and no symptomatic in-stent stenosis was found.Conclusion:Result of this study shows that PED Shield may be an effective and safe clinical option for intracranial unruptured saccular aneurysms.

Objective To establish a lung cancer risk prediction model using data mining technology and compare the performance of decision tree C5.0 and artificial neural networks in the application of risk prediction model, and to explore the value of data mining techniques in lung cancer risk prediction. Methods We collected the data of 180 patients with lung cancer and 240 patients with benign lung lesion which contained 17 variables of risk factors and clinical symptoms. Decision tree C5.0 and artificial neural networks models were established to compare the prediction performance. Results There were 420 valid samples collected in total and proportioned with the ratio of 7:3 for the training set and testing set. The accuracy, sensitivity, specificity, Youden index, positive predictive value, negative predictive value and AUC of artificial neural networks model were 65.3%, 61.7%, 73.3%, 0.350, 54.9%, 73.1% and 0.675 (95%CI: 0.628-0.720) in testing set; those of decision tree C5.0 model were 61.0%, 47.8%, 80.4%, 0.282, 35.3%, 80.6% and 0.641 (95%CI: 0.593-0.687) in testing set. Conclusion The artificial neural networks model is superior to the decision tree C5.0 model at overall performance and it has potential application value in the risk prediction of lung cancer.