Background: Periprosthetic fracture (PPF) is a troublesome complication as it utilizes substantial healthcare resources. Recent studies about the epidemiology of PPF after total knee arthroplasty (TKA) are still lacking, and there is limited national-level analysis focusing on the comorbid chronic conditions as risk factors of PPF. This study used national registry data from South Korea and aimed to investigate the epidemiology of PPF following TKA between 2010 and 2020 and identify which comorbidities contributed to the risk of PPF. Methods: Using Health Insurance Review and Assessment (HIRA) service data in South Korea, the incidence of PPF after TKA between 2010 and 2020 was evaluated and stratified by age and sex. Medical comorbidities were evaluated as possible risk factors for PPF using Cox regression analysis. Results: PPF occurred in 14,429 patients, accounting for 2.37% of total TKA patients. The prevalence of PPF by sex was 2.50% in women and 1.64% in men. The PPF rate was 2.82% in under 60 years, 2.25% in 60 to 69 years, 2.42% in 70 to 79 years, 2.29% in 80 to 89 years, and 2.12% in over 90 years. Among 17 analyzed comorbidities, 11 were found to be associated with PPF after TKA. Severe liver disease (hazard ratio [HR], 1.303), hemiplegia (HR, 1.244), and dementia (HR, 1.206) were the top 3 risk factors.Although osteoporosis, pulmonary disease, peptic ulcer, and diabetes showed relatively low HRs than these top 3 factors, the incidence rates were higher. Conclusions PPF occurred in 2.37% of TKA patients in South Korea from 2010 to 2020. PPF rate was higher in women. To prevent PPF after TKA, proper patient management and education should be emphasized, particularly in patients with severe liver disease, hemiplegia, and dementia.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Although oxidative stress is the main pathophysiology of the development of diabetic neuropathy, oral administration of antioxidants has given disappointing results. Here, we hypothesized that local delivery of antioxidants would provide protective effects on Schwann cells due to the high concentration of local lesions. We prepared alpha-tocopherol (ATF)-loaded liposomes and tested their skin penetration after sonication. An in vitro study using IMS-32 cells was conducted to determine the level of reactive oxygen species (ROS) scavenging effects of ATF-liposomes. ATF reduced ROS in high-glucose-exposed IMS-32 cells in a dosedependent manner. ATF-liposomes also reduced the ROS level in vitro and ultrasound irradiation enhanced delivery to the dermis in porcine ear skin. This study showed that it is feasible to deliver ATF through the skin and can effectively reduce ROS. This model is worthy of development for clinical use.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background: Periprosthetic fracture (PPF) is a troublesome complication as it utilizes substantial healthcare resources. Recent studies about the epidemiology of PPF after total knee arthroplasty (TKA) are still lacking, and there is limited national-level analysis focusing on the comorbid chronic conditions as risk factors of PPF. This study used national registry data from South Korea and aimed to investigate the epidemiology of PPF following TKA between 2010 and 2020 and identify which comorbidities contributed to the risk of PPF. Methods: Using Health Insurance Review and Assessment (HIRA) service data in South Korea, the incidence of PPF after TKA between 2010 and 2020 was evaluated and stratified by age and sex. Medical comorbidities were evaluated as possible risk factors for PPF using Cox regression analysis. Results: PPF occurred in 14,429 patients, accounting for 2.37% of total TKA patients. The prevalence of PPF by sex was 2.50% in women and 1.64% in men. The PPF rate was 2.82% in under 60 years, 2.25% in 60 to 69 years, 2.42% in 70 to 79 years, 2.29% in 80 to 89 years, and 2.12% in over 90 years. Among 17 analyzed comorbidities, 11 were found to be associated with PPF after TKA. Severe liver disease (hazard ratio [HR], 1.303), hemiplegia (HR, 1.244), and dementia (HR, 1.206) were the top 3 risk factors.Although osteoporosis, pulmonary disease, peptic ulcer, and diabetes showed relatively low HRs than these top 3 factors, the incidence rates were higher. Conclusions PPF occurred in 2.37% of TKA patients in South Korea from 2010 to 2020. PPF rate was higher in women. To prevent PPF after TKA, proper patient management and education should be emphasized, particularly in patients with severe liver disease, hemiplegia, and dementia.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Although oxidative stress is the main pathophysiology of the development of diabetic neuropathy, oral administration of antioxidants has given disappointing results. Here, we hypothesized that local delivery of antioxidants would provide protective effects on Schwann cells due to the high concentration of local lesions. We prepared alpha-tocopherol (ATF)-loaded liposomes and tested their skin penetration after sonication. An in vitro study using IMS-32 cells was conducted to determine the level of reactive oxygen species (ROS) scavenging effects of ATF-liposomes. ATF reduced ROS in high-glucose-exposed IMS-32 cells in a dosedependent manner. ATF-liposomes also reduced the ROS level in vitro and ultrasound irradiation enhanced delivery to the dermis in porcine ear skin. This study showed that it is feasible to deliver ATF through the skin and can effectively reduce ROS. This model is worthy of development for clinical use.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.