Purpose: Medical artificial intelligence (AI) is rapidly being integrated into clinical practice and healthcare systems, raising concerns regarding safety, accountability, and governance. Despite its increasing importance, empirical comparative studies examining differences in perceptions of medical AI among key expert groups remain limited. This study aimed to compare and analyze perceptions of medical AI among medical and non-medical professionals and to systematically identify commonalities and differences across policy- and governance-relevant domains. Methods: Focus group interviews using open-ended questions were conducted with 30 experts (15 medical and 15 non-medical professionals) who had direct experience with medical AI. Data were analyzed using inductive thematic analysis combined with qualitative comparative analysis. Analytical rigor was strengthened through independent coding and consensus-based discussions. Results: Both groups recognized the potential of medical AI to bring meaningful changes to healthcare systems. However, medical professionals primarily evaluated medical AI in terms of clinical applicability, patient safety, explainability, and accountability. In contrast, non-medical professionals emphasized technological maturity, scalability, data infrastructure, standardization, and system-integration potential. Group-specific patterns also emerged regarding perceived limitations, autonomy, educational priorities, and classification frameworks, particularly in relation to clinical risk management versus system-level design and governance considerations. Conclusion: Differences in perceptions of medical AI are systematically associated with distinct interpretive frames shaped by professional roles and responsibility structures. Effective implementation and policy design for medical AI therefore require an integrated approach that accounts for these structural differences. This study provides empirical evidence and a conceptual foundation for future quantitative and mixed-methods research on medical AI governance.

Purpose: To investigate whether using a continuous glucose monitoring (CGM) for the second time (2nd_CGM) would be effective after using it for the first time (1st_CGM), depending on age. Materials and Methods: This study included patients aged ≥40 years who were diagnosed with type 2 diabetes and had used a CGM at least twice between 2017 and 2021. Participants were divided into two groups based on their age: those aged <60 years and those aged ≥60 years. We assessed the glycemic control status of the 1st_CGM and 2nd_CGM, along with the glycemic variability. Results: Overall, 15 patients were included in the study. The mean glucose level in users aged <60 years significantly decreased (p<0.001) owing to the CGM use, while it did not increase in those aged ≥60 years. In users aged ≥60 years, the 1st_CGM group showed a significant decrease in blood glucose levels over time (p<0.05), whereas the 2nd_CGM group only showed a non-significant decreasing trend. The time in range tended to increase in those aged <60 years but decreased in those aged ≥60 years. In those aged <60 years, the mean amplitude of glycemic excursions (p<0.001), standard deviation (p<0.05), and coefficient of variation (p<0.001) significantly decreased. In those aged ≥60 years, these parameters exhibited a non-significant decreasing trend. Conclusion Glycemic effect and variability improved as expected with 1st_CGM use. However, 2nd_CGM did not significantly improve glycemic effect or variability in users aged ≥60 years, contrary to expectations. To address this issue, further investigation is needed to understand why, compared to 1st_CGM, 2nd_CGM fails to achieve better glycemic control in individuals aged ≥60 years.

Background: This study aims to identify the incidence and risk factors of periprosthetic infections following endoprosthetic reconstruction of femoral metastatic bone disease (MBD). In this population with MBD, the marked impact of infection on the patient’s systemic treatment highlights the importance of understanding both the incidence and associated risk factors. Methods: This retrospective cohort study included a total of 140 patients who underwent endoprosthetic reconstruction for femoral MBD at a tertiary referral hospital in South Korea between 2009 and 2019. Infection-free survival was estimated using the Kaplan-Meier method, and Cox proportional hazards model analyses were performed to evaluate the risk factors associated with periprosthetic infection. Results: The incidence of periprosthetic infection in patients who underwent endoprosthetic reconstruction for femoral MBD was 9% (12 out of 140 patients). Risk factors for periprosthetic infection were hepatocellular carcinoma (HCC) as the primary tumor (hazard ratio [HR], 6.08; 95% CI, 1.63–22.6; p = 0.007) and low preoperative absolute neutrophil count (HR, 6.99; 95% CI, 1.79–27.4; p = 0.005). Conclusions Patients with femoral MBD had a 9% risk of developing a periprosthetic infection. Given their limited life expectancy, this translated to a substantial rate of 58.9 infections per 1,000 person-joint-years. Possible risk factors for periprosthetic infection were low preoperative absolute neutrophil count and HCC as the primary tumor. The high incidence of periprosthetic infection and its associated risk factors should be considered in patients undergoing endoprosthetic reconstruction for femoral MBD.

Background: This study aims to identify the incidence and risk factors of periprosthetic infections following endoprosthetic reconstruction of femoral metastatic bone disease (MBD). In this population with MBD, the marked impact of infection on the patient’s systemic treatment highlights the importance of understanding both the incidence and associated risk factors. Methods: This retrospective cohort study included a total of 140 patients who underwent endoprosthetic reconstruction for femoral MBD at a tertiary referral hospital in South Korea between 2009 and 2019. Infection-free survival was estimated using the Kaplan-Meier method, and Cox proportional hazards model analyses were performed to evaluate the risk factors associated with periprosthetic infection. Results: The incidence of periprosthetic infection in patients who underwent endoprosthetic reconstruction for femoral MBD was 9% (12 out of 140 patients). Risk factors for periprosthetic infection were hepatocellular carcinoma (HCC) as the primary tumor (hazard ratio [HR], 6.08; 95% CI, 1.63–22.6; p = 0.007) and low preoperative absolute neutrophil count (HR, 6.99; 95% CI, 1.79–27.4; p = 0.005). Conclusions Patients with femoral MBD had a 9% risk of developing a periprosthetic infection. Given their limited life expectancy, this translated to a substantial rate of 58.9 infections per 1,000 person-joint-years. Possible risk factors for periprosthetic infection were low preoperative absolute neutrophil count and HCC as the primary tumor. The high incidence of periprosthetic infection and its associated risk factors should be considered in patients undergoing endoprosthetic reconstruction for femoral MBD.

Purpose: To investigate whether using a continuous glucose monitoring (CGM) for the second time (2nd_CGM) would be effective after using it for the first time (1st_CGM), depending on age. Materials and Methods: This study included patients aged ≥40 years who were diagnosed with type 2 diabetes and had used a CGM at least twice between 2017 and 2021. Participants were divided into two groups based on their age: those aged <60 years and those aged ≥60 years. We assessed the glycemic control status of the 1st_CGM and 2nd_CGM, along with the glycemic variability. Results: Overall, 15 patients were included in the study. The mean glucose level in users aged <60 years significantly decreased (p<0.001) owing to the CGM use, while it did not increase in those aged ≥60 years. In users aged ≥60 years, the 1st_CGM group showed a significant decrease in blood glucose levels over time (p<0.05), whereas the 2nd_CGM group only showed a non-significant decreasing trend. The time in range tended to increase in those aged <60 years but decreased in those aged ≥60 years. In those aged <60 years, the mean amplitude of glycemic excursions (p<0.001), standard deviation (p<0.05), and coefficient of variation (p<0.001) significantly decreased. In those aged ≥60 years, these parameters exhibited a non-significant decreasing trend. Conclusion Glycemic effect and variability improved as expected with 1st_CGM use. However, 2nd_CGM did not significantly improve glycemic effect or variability in users aged ≥60 years, contrary to expectations. To address this issue, further investigation is needed to understand why, compared to 1st_CGM, 2nd_CGM fails to achieve better glycemic control in individuals aged ≥60 years.

Background: This study aims to identify the incidence and risk factors of periprosthetic infections following endoprosthetic reconstruction of femoral metastatic bone disease (MBD). In this population with MBD, the marked impact of infection on the patient’s systemic treatment highlights the importance of understanding both the incidence and associated risk factors. Methods: This retrospective cohort study included a total of 140 patients who underwent endoprosthetic reconstruction for femoral MBD at a tertiary referral hospital in South Korea between 2009 and 2019. Infection-free survival was estimated using the Kaplan-Meier method, and Cox proportional hazards model analyses were performed to evaluate the risk factors associated with periprosthetic infection. Results: The incidence of periprosthetic infection in patients who underwent endoprosthetic reconstruction for femoral MBD was 9% (12 out of 140 patients). Risk factors for periprosthetic infection were hepatocellular carcinoma (HCC) as the primary tumor (hazard ratio [HR], 6.08; 95% CI, 1.63–22.6; p = 0.007) and low preoperative absolute neutrophil count (HR, 6.99; 95% CI, 1.79–27.4; p = 0.005). Conclusions Patients with femoral MBD had a 9% risk of developing a periprosthetic infection. Given their limited life expectancy, this translated to a substantial rate of 58.9 infections per 1,000 person-joint-years. Possible risk factors for periprosthetic infection were low preoperative absolute neutrophil count and HCC as the primary tumor. The high incidence of periprosthetic infection and its associated risk factors should be considered in patients undergoing endoprosthetic reconstruction for femoral MBD.

Purpose: To investigate whether using a continuous glucose monitoring (CGM) for the second time (2nd_CGM) would be effective after using it for the first time (1st_CGM), depending on age. Materials and Methods: This study included patients aged ≥40 years who were diagnosed with type 2 diabetes and had used a CGM at least twice between 2017 and 2021. Participants were divided into two groups based on their age: those aged <60 years and those aged ≥60 years. We assessed the glycemic control status of the 1st_CGM and 2nd_CGM, along with the glycemic variability. Results: Overall, 15 patients were included in the study. The mean glucose level in users aged <60 years significantly decreased (p<0.001) owing to the CGM use, while it did not increase in those aged ≥60 years. In users aged ≥60 years, the 1st_CGM group showed a significant decrease in blood glucose levels over time (p<0.05), whereas the 2nd_CGM group only showed a non-significant decreasing trend. The time in range tended to increase in those aged <60 years but decreased in those aged ≥60 years. In those aged <60 years, the mean amplitude of glycemic excursions (p<0.001), standard deviation (p<0.05), and coefficient of variation (p<0.001) significantly decreased. In those aged ≥60 years, these parameters exhibited a non-significant decreasing trend. Conclusion Glycemic effect and variability improved as expected with 1st_CGM use. However, 2nd_CGM did not significantly improve glycemic effect or variability in users aged ≥60 years, contrary to expectations. To address this issue, further investigation is needed to understand why, compared to 1st_CGM, 2nd_CGM fails to achieve better glycemic control in individuals aged ≥60 years.

Purpose: To investigate whether using a continuous glucose monitoring (CGM) for the second time (2nd_CGM) would be effective after using it for the first time (1st_CGM), depending on age. Materials and Methods: This study included patients aged ≥40 years who were diagnosed with type 2 diabetes and had used a CGM at least twice between 2017 and 2021. Participants were divided into two groups based on their age: those aged <60 years and those aged ≥60 years. We assessed the glycemic control status of the 1st_CGM and 2nd_CGM, along with the glycemic variability. Results: Overall, 15 patients were included in the study. The mean glucose level in users aged <60 years significantly decreased (p<0.001) owing to the CGM use, while it did not increase in those aged ≥60 years. In users aged ≥60 years, the 1st_CGM group showed a significant decrease in blood glucose levels over time (p<0.05), whereas the 2nd_CGM group only showed a non-significant decreasing trend. The time in range tended to increase in those aged <60 years but decreased in those aged ≥60 years. In those aged <60 years, the mean amplitude of glycemic excursions (p<0.001), standard deviation (p<0.05), and coefficient of variation (p<0.001) significantly decreased. In those aged ≥60 years, these parameters exhibited a non-significant decreasing trend. Conclusion Glycemic effect and variability improved as expected with 1st_CGM use. However, 2nd_CGM did not significantly improve glycemic effect or variability in users aged ≥60 years, contrary to expectations. To address this issue, further investigation is needed to understand why, compared to 1st_CGM, 2nd_CGM fails to achieve better glycemic control in individuals aged ≥60 years.

Purpose: To investigate whether using a continuous glucose monitoring (CGM) for the second time (2nd_CGM) would be effective after using it for the first time (1st_CGM), depending on age. Materials and Methods: This study included patients aged ≥40 years who were diagnosed with type 2 diabetes and had used a CGM at least twice between 2017 and 2021. Participants were divided into two groups based on their age: those aged <60 years and those aged ≥60 years. We assessed the glycemic control status of the 1st_CGM and 2nd_CGM, along with the glycemic variability. Results: Overall, 15 patients were included in the study. The mean glucose level in users aged <60 years significantly decreased (p<0.001) owing to the CGM use, while it did not increase in those aged ≥60 years. In users aged ≥60 years, the 1st_CGM group showed a significant decrease in blood glucose levels over time (p<0.05), whereas the 2nd_CGM group only showed a non-significant decreasing trend. The time in range tended to increase in those aged <60 years but decreased in those aged ≥60 years. In those aged <60 years, the mean amplitude of glycemic excursions (p<0.001), standard deviation (p<0.05), and coefficient of variation (p<0.001) significantly decreased. In those aged ≥60 years, these parameters exhibited a non-significant decreasing trend. Conclusion Glycemic effect and variability improved as expected with 1st_CGM use. However, 2nd_CGM did not significantly improve glycemic effect or variability in users aged ≥60 years, contrary to expectations. To address this issue, further investigation is needed to understand why, compared to 1st_CGM, 2nd_CGM fails to achieve better glycemic control in individuals aged ≥60 years.

Background: This study aims to identify the incidence and risk factors of periprosthetic infections following endoprosthetic reconstruction of femoral metastatic bone disease (MBD). In this population with MBD, the marked impact of infection on the patient’s systemic treatment highlights the importance of understanding both the incidence and associated risk factors. Methods: This retrospective cohort study included a total of 140 patients who underwent endoprosthetic reconstruction for femoral MBD at a tertiary referral hospital in South Korea between 2009 and 2019. Infection-free survival was estimated using the Kaplan-Meier method, and Cox proportional hazards model analyses were performed to evaluate the risk factors associated with periprosthetic infection. Results: The incidence of periprosthetic infection in patients who underwent endoprosthetic reconstruction for femoral MBD was 9% (12 out of 140 patients). Risk factors for periprosthetic infection were hepatocellular carcinoma (HCC) as the primary tumor (hazard ratio [HR], 6.08; 95% CI, 1.63–22.6; p = 0.007) and low preoperative absolute neutrophil count (HR, 6.99; 95% CI, 1.79–27.4; p = 0.005). Conclusions Patients with femoral MBD had a 9% risk of developing a periprosthetic infection. Given their limited life expectancy, this translated to a substantial rate of 58.9 infections per 1,000 person-joint-years. Possible risk factors for periprosthetic infection were low preoperative absolute neutrophil count and HCC as the primary tumor. The high incidence of periprosthetic infection and its associated risk factors should be considered in patients undergoing endoprosthetic reconstruction for femoral MBD.