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.

Purpose: In men with metastatic castration-resistant prostate cancer (mCRPC), new bone lesions are sometimes not properly categorized through a confirmatory bone scan, and clinical significance of the test itself remains unclear. This study aimed to demonstrate the performance rate of confirmatory bone scans in a real-world setting and their prognostic impact in enzalutamide-treated mCRPC. Materials and Methods: Patients who received oral enzalutamide for mCRPC during 2014-2017 at 14 tertiary centers in Korea were included. Patients lacking imaging assessment data or insufficient drug exposure were excluded. The primary outcome was overall survival (OS). Secondary outcomes included performance rate of confirmatory bone scans in a real-world setting. Kaplan-Meier analysis and multivariate Cox regression analysis were performed. Results: Overall, 520 patients with mCRPC were enrolled (240 [26.2%] chemotherapy-naïve and 280 [53.2%] after chemotherapy). Among 352 responders, 92 patients (26.1%) showed new bone lesions in their early bone scan. Confirmatory bone scan was performed in 41 patients (44.6%), and it was associated with prolonged OS in the entire population (median, 30.9 vs. 19.7 months; p < 0.001), as well as in the chemotherapy-naïve (median, 47.2 vs. 20.5 months; p=0.011) and post-chemotherapy sub-groups (median, 25.5 vs. 18.0 months; p=0.006). Multivariate Cox regression showed that confirmatory bone scan performance was an independent prognostic factor for OS (hazard ratio 0.35, 95% confidence interval, 0.18 to 0.69; p=0.002). Conclusion Confirmatory bone scan performance was associated with prolonged OS. Thus, the premature discontinuation of enzalutamide without confirmatory bone scans should be discouraged.

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/Aims: To determine the association between evolutionary changes in metabolic dysfunction-associated steatotic liver disease (MASLD) status and the risk of hepatocellular carcinoma (HCC) in a nationwide population-based cohort. Methods: Information on study participants was derived from the Korea National Health Insurance Service database. The study population consisted of 5,080,410 participants who underwent two consecutive biennial health screenings between 2009 and 2012. All participants were followed up until HCC, death, or 31 December 2020. The association of evolutionary changes in MASLD status, as assessed by the fatty liver index and cardiometabolic risk factors, including persistent non-MASLD, resolved MASLD, incident MASLD, and persistent MASLD, with HCC risk was evaluated using multivariable-adjusted Cox proportional hazards regression. Results: Among the 5,080,410 participants with 39,910,331 person-years of follow-up, 4,801 participants developed HCC. The incidence of HCC in participants with resolved, incident, and persistent MASLD was approximately 2.2-, 2.3-, and 4.7-fold higher, respectively, than that in those with persistent non-MASLD among the Korean adult population. When stratifying the participants according to the evolutionary change in MASLD status, persistent (adjusted hazard ratio [aHR], 2.94; 95% confidence interval [CI], 2.68–3.21; P<0.001), incident (aHR, 1.85; 95% CI, 1.63–2.10; P<0.001), and resolved MASLD (aHR, 1.33; 95% CI, 1.18–1.50; P<0.001) had an increased risk of HCC compared to persistent non-MASLD. Conclusions The evolutionary changes in MASLD were associated with the differential risk of HCC independent of metabolic risk factors and concomitant medications, providing additional information on the risk of HCC stratification in patients with MASLD.

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.

Live-born cases of partial trisomy 12q are rare, and only a few fetuses with this unbalanced translocation have survived to term. To our knowledge, only about 40 patients have been reported as having 12q duplication, and among them are no Korean reports. Here, we report the first Korean case of siblings with a 12q24.22q24.33 duplication. An 11-year-old boy visited our clinic for short stature. He was born small for his gestational age and had distinctive facial features, a history of surgery for anorectal malformation, psychomotor delay, intellectual disabilities, and attention-deficit/hyperactivity disorder (ADHD). He had an older sister with similar clinical features. The chromosomal microarray of the patient and his sister showed identical results: a 16.2 Mb duplication of 12q24.22q24.33. They had an identical cutoff point, but their symptoms were not. Symptoms common to both included growth retardation, psychomotor delay, intellectual disability, ADHD, and small for their gestational age.