The metaverse, a 3-dimensional digital platform that enables users to interact and engage in realistic virtual activities beyond time and space limitations, has garnered significant investment across industries, particularly in healthcare. In the medical field, the metaverse shows promise as a digital therapeutic platform to enhance interaction between medical professionals and patients. Concurrently, generative artificial intelligence, especially large language models, is being integrated into healthcare for applications in data analysis, image recognition, and natural language processing. In urology, large language models (LLMs) support are increasingly used in urology for tasks such as image diagnosis, data processing, patient education, and treatment assistance in order to provide significant support in clinical settings. By combining LLMs with the immersive capabilities of the metaverse, new possibilities emerge to improve urologic treatment in areas that require consistent treatments, habit formation, and long-term management. This paper reviews current research and applications of LLMs in urology, discusses the challenges associated with their use including data quality, bias, security, and ethical issues, and explores the need for regulatory standards. Furthermore, it highlights the potential of a metaverse-based digital platform to improve urologic care and streamline information exchange to maximize the benefits of this integrated approach in future healthcare applications.

The metaverse, a 3-dimensional digital platform that enables users to interact and engage in realistic virtual activities beyond time and space limitations, has garnered significant investment across industries, particularly in healthcare. In the medical field, the metaverse shows promise as a digital therapeutic platform to enhance interaction between medical professionals and patients. Concurrently, generative artificial intelligence, especially large language models, is being integrated into healthcare for applications in data analysis, image recognition, and natural language processing. In urology, large language models (LLMs) support are increasingly used in urology for tasks such as image diagnosis, data processing, patient education, and treatment assistance in order to provide significant support in clinical settings. By combining LLMs with the immersive capabilities of the metaverse, new possibilities emerge to improve urologic treatment in areas that require consistent treatments, habit formation, and long-term management. This paper reviews current research and applications of LLMs in urology, discusses the challenges associated with their use including data quality, bias, security, and ethical issues, and explores the need for regulatory standards. Furthermore, it highlights the potential of a metaverse-based digital platform to improve urologic care and streamline information exchange to maximize the benefits of this integrated approach in future healthcare applications.

The metaverse, a 3-dimensional digital platform that enables users to interact and engage in realistic virtual activities beyond time and space limitations, has garnered significant investment across industries, particularly in healthcare. In the medical field, the metaverse shows promise as a digital therapeutic platform to enhance interaction between medical professionals and patients. Concurrently, generative artificial intelligence, especially large language models, is being integrated into healthcare for applications in data analysis, image recognition, and natural language processing. In urology, large language models (LLMs) support are increasingly used in urology for tasks such as image diagnosis, data processing, patient education, and treatment assistance in order to provide significant support in clinical settings. By combining LLMs with the immersive capabilities of the metaverse, new possibilities emerge to improve urologic treatment in areas that require consistent treatments, habit formation, and long-term management. This paper reviews current research and applications of LLMs in urology, discusses the challenges associated with their use including data quality, bias, security, and ethical issues, and explores the need for regulatory standards. Furthermore, it highlights the potential of a metaverse-based digital platform to improve urologic care and streamline information exchange to maximize the benefits of this integrated approach in future healthcare applications.

Objective: Fall from height (FFH) is a major public health problem that can result in severe injury, disability, and death. This study investigated how the characteristics of jumpers and fallers differ. Methods: This was a retrospective study of FFH patients enrolled in an Emergency Department-based Injury In-depth Surveillance (EDIIS) registry between 2011 and 2018. Depending on whether the injury was intentional, FFH patients who had fallen from a height of at least 1 m were divided into two groups: jumpers and fallers. Patient characteristics, organ damage, and death were compared between the two groups, and factors that significantly affected death were identified using multivariable logistic analysis. Results: Among 39,419 patients, 1,982 (5.0%) were jumpers. Of the jumpers, 977 (49.3%) were male, while 30,643 (81.9%) of fallers were male. The jumper group had the highest number of individuals in their 20s, with the number decreasing as age increased. In contrast, the number of individuals in the faller group rose until reaching their 50s, after which it declined. More thoracoabdominal, spinal, and brain injuries were found in jumpers. The in-hospital mortality of jumpers and fallers was 832 (42.0%) and 1,268 (3.4%), respectively. Intentionality was a predictor of in-hospital mortality, along with sex, age, and fall height, with an odds ratio of 7.895 (95% confidence interval, 6.746–9.240). Conclusion Jumpers and fallers have different epidemiological characteristics, and jumpers experienced a higher degree of injury and mortality than fallers. Differentiated prevention and treatment strategies are needed for jumpers and fallers to reduce mortality in FFH patients.

Background: Atherogenic dyslipidemia, which is frequently associated with type 2 diabetes (T2D) and insulin resistance, contributes to the development of vascular complications. Statin therapy is the primary approach to dyslipidemia management in T2D, however, the role of non-statin therapy remains unclear. Ezetimibe reduces cholesterol burden by inhibiting intestinal cholesterol absorption. Fibrates lower triglyceride levels and increase high-density lipoprotein cholesterol (HDL-C) levels via peroxisome proliferator- activated receptor alpha agonism. Therefore, when combined, these drugs effectively lower non-HDL-C levels. Despite this, few clinical trials have specifically targeted non-HDL-C, and the efficacy of triple combination therapies, including statins, ezetimibe, and fibrates, has yet to be determined. Methods: This is a multicenter, prospective, randomized, open-label, active-comparator controlled trial involving 3,958 eligible participants with T2D, cardiovascular risk factors, and elevated non-HDL-C (≥100 mg/dL). Participants, already on moderate-intensity statins, will be randomly assigned to either Ezefeno (ezetimibe/fenofibrate) addition or statin dose-escalation. The primary end point is the development of a composite of major adverse cardiovascular and diabetic microvascular events over 48 months. Conclusion This trial aims to assess whether combining statins, ezetimibe, and fenofibrate is as effective as, or possibly superior to, statin monotherapy intensification in lowering cardiovascular and microvascular disease risk for patients with T2D. This could propose a novel therapeutic approach for managing dyslipidemia in T2D.

This paper examines the use of serious games that integrate engaging gameplay with educational and therapeutic benefits with a particular focus on their application in urology. The study reviews both domestic and international cases to evaluate the current practices and implications of these digital therapies. While serious games have been widely utilized in the treatment of pediatric cancer and psychiatric disorders—areas that require long-term care and management—their application in urology, in particular pediatric urology, has been limited. Although digital therapies like serious games are still emerging in the field of urology, they hold promise as effective supplements to traditional treatments while offering new options for managing a range of urological conditions. Pediatric conditions such as bedwetting, urinary incontinence, and dysuria, which often benefit from long-term training and habit formation, are particularly well-suited to this approach. By helping pediatric patients better understand and manage their symptoms, serious games can play a supportive role in the treatment process and have shown positive medical outcomes. This paper reviews the definitions and therapeutic effects of serious games, analyzes their current use in the medical field, and argues for their increased application in treating pediatric urinary conditions.

Background: This study aimed to generate a Z score calculation model for coronary artery diameter of normal children and adolescents to be adopted as the standard calculation method with consensus in clinical practice. Methods: This study was a retrospective, multicenter study that collected data from multiple institutions across South Korea. Data were analyzed to determine the model that best fit the relationship between the diameter of coronary arteries and independent demographic parameters. Linear, power, logarithmic, exponential, and square root polynomial models were tested for best fit. Results: Data of 2,030 subjects were collected from 16 institutions. Separate calculation models for each sex were developed because the impact of demographic variables on the diameter of coronary arteries differs according to sex. The final model was the polynomial formula with an exponential relationship between the diameter of coronary arteries and body surface area using the DuBois formula. Conclusion A new coronary artery diameter Z score model was developed and is anticipated to be applicable in clinical practice. The new model will help establish a consensus-based Z score model.

Background: Over the last decade, extracorporeal membrane oxygenation (ECMO) use in critically ill children has increased and is associated with favorable outcomes. Our study aims to evaluate the current status of pediatric ECMO in Korea, with a specific focus on its volume and changes in survival rates based on diagnostic indications. Methods: This multicenter study retrospectively analyzed the indications and outcomes of pediatric ECMO over 10 years in patients at 14 hospitals in Korea from January 2012 to December 2021. Four diagnostic categories (neonatal respiratory, pediatric respiratory, postcardiotomy, and cardiac-medical) and trends were compared between periods 1 (2012–2016) and 2 (2017–2021). Results: Overall, 1065 ECMO runs were performed on 1032 patients, with the annual number of cases remaining unchanged over the 10 years. ECMO was most frequently used for post-cardiotomy (42.4%), cardiac-medical (31.8%), pediatric respiratory (17.5%), and neonatal respiratory (8.2%) cases. A 3.7% increase and 6.1% decrease in pediatric respiratory and post-cardiotomy cases, respectively, were noted between periods 1 and 2.Among the four groups, the cardiac-medical group had the highest survival rate (51.2%), followed by the pediatric respiratory (46.4%), post-cardiotomy (36.5%), and neonatal respiratory (29.4%) groups. A consistent improvement was noted in patient survival over the 10 years, with a significant increase between the two periods from 38.2% to 47.1% (P = 0.004). Improvement in survival was evident in post-cardiotomy cases (30–45%, P = 0.002).Significant associations with mortality were observed in neonates, patients requiring dialysis, and those treated with extracorporeal cardiopulmonary resuscitation (P < 0.001). In pediatric respiratory ECMO, immunocompromised patients also showed a significant correlation with mortality (P < 0.001). Conclusion Pediatric ECMO demonstrated a steady increase in overall survival in Korea;however, further efforts are needed since the outcomes remain suboptimal compared with global outcomes.

Background: Korea recently established 70 emergency medical service areas. However, there are many concerns that medical resources for stroke could not be evenly distributed through the country. We aimed to compare the treatment quality and outcomes of acute stroke among the emergency medical service areas. Methods: This study analyzed the data of 28,800 patients admitted in 248 hospitals which participated in the 8th acute stroke quality assessment by Health Insurance Review and Assessment Service. Individual hospitals were regrouped into emergency service areas according to the address of the location. Assessment indicators and fatality were compared by the service areas. We defined the appropriate hospital by the performance of intravenous thrombolysis. Results: In seven service areas, there were no hospitals which received more than 10 stroke patients for 6 months. In nine service areas, there were no patients who underwent intravenous thrombolysis (IVT). Among 167 designated emergency medical centers, 50 hospitals (29.9%) responded that IVT was impossible 24 hours a day. There are 97 (39.1%) hospitals that meet the definitions of appropriate hospital. In 23 service areas (32.9%) had no appropriate or feasible hospitals. The fatality of service areas with stroke centers were 6.9% within 30 days and 15.6% within 1 year from stroke onset than those without stroke centers (7.7%, 16.9%, respectively). Conclusions There was a wide regional gap in the medical resource and the quality of treatments for acute stroke among emergency medical service areas in Korea. The poststroke fatality rate of the service areas which have stroke centers or appropriate hospitals were significantly low.

Background: Cardiac resynchronization therapy (CRT) is an effective treatment option for patients with heart failure (HF) and left ventricular (LV) dyssynchrony. However, the problem of some patients not responding to CRT remains unresolved. This study aimed to propose a novel in silico method for CRT simulation. Methods: Three-dimensional heart geometry was constructed from computed tomography images. The finite ele‑ ment method was used to elucidate the electric wave propagation in the heart. The electric excitation and mechani‑ cal contraction were coupled with vascular hemodynamics by the lumped parameter model. The model parameters for three-dimensional (3D) heart and vascular mechanics were estimated by matching computed variables with measured physiological parameters. CRT effects were simulated in a patient with HF and left bundle branch block (LBBB). LV end-diastolic (LVEDV) and end-systolic volumes (LVESV), LV ejection fraction (LVEF), and CRT responsiveness measured from the in silico simulation model were compared with those from clinical observation. A CRT responder was defined as absolute increase in LVEF ≥ 5% or relative increase in LVEF ≥ 15%. Results: A 68-year-old female with nonischemic HF and LBBB was retrospectively included. The in silico CRT simu‑ lation modeling revealed that changes in LVEDV, LVESV, and LVEF by CRT were from 174 to 173 mL, 116 to 104 mL, and 33 to 40%, respectively. Absolute and relative ΔLVEF were 7% and 18%, respectively, signifying a CRT responder.In clinical observation, echocardiography showed that changes in LVEDV, LVESV, and LVEF by CRT were from 162 to 119 mL, 114 to 69 mL, and 29 to 42%, respectively. Absolute and relative ΔLVESV were 13% and 31%, respectively, also signifying a CRT responder. CRT responsiveness from the in silico CRT simulation model was concordant with that in the clinical observation. Conclusion This in silico CRT simulation method is a feasible technique to screen for CRT non-responders in patients with HF and LBBB.