Objective To investigate the effect of 3D technology combined with smartphones in problem-based learning(PBL)for neuroendoscopy.Methods 82 trainees who were enrolled from January 2021 to January 2023 were selected as the research subjects.A randomized controlled trial was conducted,and the subjects were divided into a control group and an experimental group.PBL and 3D technology combined with smartphone-assisted PBL were implemented respectively for two groups of students.The data were analyzed using t-test.Teaching satisfac-tion is evaluated by 2 test.Results The results of the in-operation examination and theoretical examination of the ex-perimental group students were found to be higher than those of the control group students(t=8.630,6.087,P＜0.001),the satisfaction scores of students and teachers showing that the satisfaction of the experimental group was higher than that of the control group(x2=4.213,6.301,7.026,P＜0.01).Conclusion In the PBL of neuroendosco-py,the use of 3D technology combined with smart phones as an auxiliary teaching system can effectively improve students'sense of participation,reduce the difficulty of skull base anatomy learning,and improve students'theo-retical and surgical assessment scores and teaching satisfaction.

Objective In the clinical teaching of neurosurgery,the traditional Problem-Based Learning(PBL)teaching model faces systematic challenges such as the disconnection between the training cycle of specialized talents and technological iteration,the limitation of practical opportunities due to hospital infections,and the inefficient allocation of teaching resources.It provides a new path for teaching reform based on the deep integration of Artificial Intelligence and PBL,but it still needs to address issues such as differences in intern participation,insufficient technical adaptability of instructors,and fragmented resource allocation.Based on these problems,a collaborative mechanism of"technology development-talent cultivation"and a multi-dimensional optimization path of"intern participation-instructor training-hospital resource input"are proposed.On this basis,through collaborative strategies such as strengthening the incentive mechanism for autonomous learning,establishing a standardized instructor training system,and building a dynamic resource allocation platform,the management of neurosurgery clinical teaching is promoted towards intelligence,personalization,and systematization.

Objective:To explore the impact of metabolic syndrome in conjunction with hyperuricemia on the risk of new-onset cardiovascular disease.Methods:This study was a prospective cohort study. From June 2006 to October 2007, employees of Kailuan Group in Tangshan City, Hebei Province were selected as the research subjects. Participants were divided into four groups based on the presence or absence of metabolic syndrome and hyperuricemia. The groups include the normal group, pure hyperuricemia group, pure metabolic syndrome group, and the metabolic syndrome combined with hyperuricemia group. Four groups of participants were followed up, the primary endpoint was the occurrence of a first-ever cardiovascular disease event, including stroke and myocardial infarction. The cumulative incidence rates of cardiovascular disease in different groups during the continuous follow-up period were calculated using the Kaplan-Meier method, and the differences in cumulative incidence rates among groups were compared using the log-rank test. Multivariate Cox regression analysis was used to analyze the effect of hyperuricemia combined with metabolic syndrome on the risk of cardiovascular disease. The likelihood ratio test was used to analyze whether there was a multiplicative interaction and additive interaction between hyperuricemia and metabolic syndrome.Results:A total of 82 780 individuals were included, aged (51.5±12.6) years, and 68 622 (82.90%) were males, with a median follow-up of 14.97 years. Kaplan-Meier survival curve analysis showed that the cumulative incidence of cardiovascular disease was the highest in the metabolic syndrome combined with hyperuricemia group (log-rank P<0.001). Multivariate Cox regression analysis indicated that after adjusting for various confounding factors, the HR value and 95% CI of cardiovascular disease in the metabolic syndrome combined with hyperuricemia group were 1.24 (1.12-1.38) compared with the normal group, which were higher than those in the pure hyperuricemia group and the pure metabolic syndrome group alone. The effect of metabolic syndrome combined with hyperuricemia on the risk of cardiovascular disease demonstrated an additive effect (relative excess risk of interaction: 0.18(0.11-0.25), attributable proportion due to interaction: 0.14(0.09-0.19)). Conclusions:The combination of hyperuricemia and metabolic syndrome is an independent risk factor for cardiovascular disease. Compared to pure metabolic syndrome or hyperuricemia alone, the impact of metabolic syndrome combined with hyperuricemia on cardiovascular disease is more significant.

Objective:To evaluate the diagnostic value of MRI findings in differentiating between tophus and giant cell tumors of the tendon sheath (GCTTS) in the knee.Methods:The study was a case-control study. The clinical and MRI data of patients diagnosed with knee tophus or GCTTS was retrospectively analyzed at the Affiliated Hospital of Qingdao University from September 2018 to September 2024. The study included 23 cases of tophus and 22 cases of GCTTS. MRI sequences, including T 1WI, fat-suppressed T 2WI, and proton density weighted imaging, were evaluated. Parameters including lesion signal intensity and homogeneity, margin, maximum diameter, location (inside or outside the synovial cavity), ligament/tendon involvement, ligament/tendon parenchymal changes, adjacent bone erosion, bone marrow edema, synovial hyperplasia, joint effusion, and periarticular soft tissue swelling were recorded. Independent sample t-tests, χ2 tests, or Fisher exact tests were used to compare MRI findings between the two groups. Multivariate logistic regression was performed to identify independent predictive factors. Results:Significant differences in terms of maximum diameter, location (inside or outside the synovial cavity), ligament/tendon involvement, ligament/tendon parenchymal changes, adjacent bone erosion, bone marrow edema, and periarticular soft tissue swelling between the two groups were found (all P<0.05). No significant differences for other parameters were observed (all P>0.05). Lesion location and ligament/tendon parenchymal involvement demonstrated the highest sensitivity and specificity for distinguishing the two diseases. The sensitivity and specificity values for lesion location were 0.78 and 0.95. The sensitivity and specificity values for ligament/tendon involvement were 0.78 and 1.00. Multivariate logistic regression identified lesion location (inside or outside the synovial cavity) as an independent predictor for differentiating tophus from GCTTS ( OR=31.48, 95% CI 1.58-625.69, P=0.024). Conclusion:The location of the lesion (inside or outside the synovial cavity) and involvement of ligament/tendon parenchyma are critical factors in differentiating knee tophus from GCTTS. Additionally, lesion location serves as an independent predictor for distinguishing between the two conditions.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

Objective To investigate the effect of 3D technology combined with smartphones in problem-based learning(PBL)for neuroendoscopy.Methods 82 trainees who were enrolled from January 2021 to January 2023 were selected as the research subjects.A randomized controlled trial was conducted,and the subjects were divided into a control group and an experimental group.PBL and 3D technology combined with smartphone-assisted PBL were implemented respectively for two groups of students.The data were analyzed using t-test.Teaching satisfac-tion is evaluated by 2 test.Results The results of the in-operation examination and theoretical examination of the ex-perimental group students were found to be higher than those of the control group students(t=8.630,6.087,P＜0.001),the satisfaction scores of students and teachers showing that the satisfaction of the experimental group was higher than that of the control group(x2=4.213,6.301,7.026,P＜0.01).Conclusion In the PBL of neuroendosco-py,the use of 3D technology combined with smart phones as an auxiliary teaching system can effectively improve students'sense of participation,reduce the difficulty of skull base anatomy learning,and improve students'theo-retical and surgical assessment scores and teaching satisfaction.

Objective In the clinical teaching of neurosurgery,the traditional Problem-Based Learning(PBL)teaching model faces systematic challenges such as the disconnection between the training cycle of specialized talents and technological iteration,the limitation of practical opportunities due to hospital infections,and the inefficient allocation of teaching resources.It provides a new path for teaching reform based on the deep integration of Artificial Intelligence and PBL,but it still needs to address issues such as differences in intern participation,insufficient technical adaptability of instructors,and fragmented resource allocation.Based on these problems,a collaborative mechanism of"technology development-talent cultivation"and a multi-dimensional optimization path of"intern participation-instructor training-hospital resource input"are proposed.On this basis,through collaborative strategies such as strengthening the incentive mechanism for autonomous learning,establishing a standardized instructor training system,and building a dynamic resource allocation platform,the management of neurosurgery clinical teaching is promoted towards intelligence,personalization,and systematization.

Objective:To evaluate the diagnostic value of MRI findings in differentiating between tophus and giant cell tumors of the tendon sheath (GCTTS) in the knee.Methods:The study was a case-control study. The clinical and MRI data of patients diagnosed with knee tophus or GCTTS was retrospectively analyzed at the Affiliated Hospital of Qingdao University from September 2018 to September 2024. The study included 23 cases of tophus and 22 cases of GCTTS. MRI sequences, including T 1WI, fat-suppressed T 2WI, and proton density weighted imaging, were evaluated. Parameters including lesion signal intensity and homogeneity, margin, maximum diameter, location (inside or outside the synovial cavity), ligament/tendon involvement, ligament/tendon parenchymal changes, adjacent bone erosion, bone marrow edema, synovial hyperplasia, joint effusion, and periarticular soft tissue swelling were recorded. Independent sample t-tests, χ2 tests, or Fisher exact tests were used to compare MRI findings between the two groups. Multivariate logistic regression was performed to identify independent predictive factors. Results:Significant differences in terms of maximum diameter, location (inside or outside the synovial cavity), ligament/tendon involvement, ligament/tendon parenchymal changes, adjacent bone erosion, bone marrow edema, and periarticular soft tissue swelling between the two groups were found (all P<0.05). No significant differences for other parameters were observed (all P>0.05). Lesion location and ligament/tendon parenchymal involvement demonstrated the highest sensitivity and specificity for distinguishing the two diseases. The sensitivity and specificity values for lesion location were 0.78 and 0.95. The sensitivity and specificity values for ligament/tendon involvement were 0.78 and 1.00. Multivariate logistic regression identified lesion location (inside or outside the synovial cavity) as an independent predictor for differentiating tophus from GCTTS ( OR=31.48, 95% CI 1.58-625.69, P=0.024). Conclusion:The location of the lesion (inside or outside the synovial cavity) and involvement of ligament/tendon parenchyma are critical factors in differentiating knee tophus from GCTTS. Additionally, lesion location serves as an independent predictor for distinguishing between the two conditions.

Objective:To explore the impact of metabolic syndrome in conjunction with hyperuricemia on the risk of new-onset cardiovascular disease.Methods:This study was a prospective cohort study. From June 2006 to October 2007, employees of Kailuan Group in Tangshan City, Hebei Province were selected as the research subjects. Participants were divided into four groups based on the presence or absence of metabolic syndrome and hyperuricemia. The groups include the normal group, pure hyperuricemia group, pure metabolic syndrome group, and the metabolic syndrome combined with hyperuricemia group. Four groups of participants were followed up, the primary endpoint was the occurrence of a first-ever cardiovascular disease event, including stroke and myocardial infarction. The cumulative incidence rates of cardiovascular disease in different groups during the continuous follow-up period were calculated using the Kaplan-Meier method, and the differences in cumulative incidence rates among groups were compared using the log-rank test. Multivariate Cox regression analysis was used to analyze the effect of hyperuricemia combined with metabolic syndrome on the risk of cardiovascular disease. The likelihood ratio test was used to analyze whether there was a multiplicative interaction and additive interaction between hyperuricemia and metabolic syndrome.Results:A total of 82 780 individuals were included, aged (51.5±12.6) years, and 68 622 (82.90%) were males, with a median follow-up of 14.97 years. Kaplan-Meier survival curve analysis showed that the cumulative incidence of cardiovascular disease was the highest in the metabolic syndrome combined with hyperuricemia group (log-rank P<0.001). Multivariate Cox regression analysis indicated that after adjusting for various confounding factors, the HR value and 95% CI of cardiovascular disease in the metabolic syndrome combined with hyperuricemia group were 1.24 (1.12-1.38) compared with the normal group, which were higher than those in the pure hyperuricemia group and the pure metabolic syndrome group alone. The effect of metabolic syndrome combined with hyperuricemia on the risk of cardiovascular disease demonstrated an additive effect (relative excess risk of interaction: 0.18(0.11-0.25), attributable proportion due to interaction: 0.14(0.09-0.19)). Conclusions:The combination of hyperuricemia and metabolic syndrome is an independent risk factor for cardiovascular disease. Compared to pure metabolic syndrome or hyperuricemia alone, the impact of metabolic syndrome combined with hyperuricemia on cardiovascular disease is more significant.