The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

Purpose: The gonadotropin-releasing hormone (GnRH) stimulation test is the gold standard for diagnosing central precocious puberty (CPP). Gonadorelin (Relefact) is used for the test but is not always readily available; triptorelin is used as an alternative. The purpose of this study was to evaluate the diagnostic validity of the triptorelin test compared with the GnRH test in the diagnosis of CPP in girls. Methods: This retrospective study included 100 girls with premature thelarche (PT) who underwent a hypothalamic-pituitary-gonadal axis evaluation. In the overall group, 50 girls were tested with intravenous gonadorelin (Relefact) and 50 girls were tested with subcutaneous triptorelin acetate (Decapeptyl). Luteinizing hormone (LH) and follicle-stimulating hormone levels were measured at baseline and 30, 45, 60, and 90 minutes after gonadorelin injection or 30, 60, 90, and 120 minutes after triptorelin injection. Results: Clinical characteristics of age, height, weight, body mass index, and bone age were similar between the 2 groups. The highest LH level was reached 60 minutes after stimulation in both groups. Approximately 20% of the gonadorelin group and 24% of the triptorelin group were diagnosed with CPP (P=0.52). Among those diagnosed with CPP, the mean peak LH concentrations were 8.15 mIU/mL and 9.73 mIU/mL in the gonadorelin and triptorelin groups, respectively. Conclusion The triptorelin test showed similar trends of LH elevation and diagnostic rate compared with the traditional GnRH test for diagnosing CPP. This suggests that the triptorelin test may be a valid alternative to the GnRH test for differentiating CPP from self-limiting PT. Our study also demonstrated that a triptorelin stimulation test for up to 120 minutes was sufficient to diagnose CPP.

Purpose: Three-month gonadotropin-releasing hormone agonists (GnRHas) are expected to achieve better compliance in patients with central precocious puberty (CPP) compared to the monthly formulation. However, 1-month depot remains the dominant choice for conventional treatment worldwide. Our study aimed to investigate the long-term efficacy of a 3-month GnRHa for CPP treatment. Methods: In this retrospective study, 69 Korean girls with CPP were prescribed either triptorelin pamoate (TP) 3-month depot (n=29) or triptorelin acetate (TA) 1-month depot (n=40) and were followed for 1 year after the end of treatment. Auxological, radiological, and biochemical data were collected every 6 months. Results: Baseline characteristics were similar between the 2 groups. In the TP 3-month depot group, 27 of 29 patients (93.1%) exhibited suppressed luteinizing hormone level (below 2.5 IU/L) after 6 months of treatment, and this suppression level was reserved until the final injection. The degree of bone age advancement in the TP 3-month depot group decreased from 1.8±0.4 years at the start of treatment to 0.6±0.5 years at 1-year posttreatment. The gain in predicted adult height (PAH) 1 year after the end of treatment was similar between the TP 3-month and TA 1-month depot groups (5.2±3.1 and 5.3±2.4 cm, respectively; p=0.875). Conclusion A 3-month depot of triptorelin effectively inhibited gonadal and sex hormones, suppressed bone maturation, and increased PAH. For patient convenience, we suggest a 3-month GnRHa regimen as a promising CPP treatment option.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Background: It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia. Methods: This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment. Results: After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events. Conclusion The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Purpose: Self-management of diabetes is a significant challenge. This study aimed to assess diabetes self-care activities and barriers among Korean young adults with diabetes mellitus. Materials and Methods: This study recruited 209 Korean adults with diabetes, with an onset age of 20–39 years, from four university hospitals. Demographic characteristics and the Summary of Diabetes Self-Care Activities (SDSCA) measure and Diabetes Self-Care Barriers Assessment Scale for Older Adults (DSCB-OA) scores were assessed using questionnaires. Results: The average age of study participants was 32.9±6.1 years. Their self-care activities, including adherence to recommended diabetes medication (5.6±2.4) and number of diabetes pills (5.5±2.3) in the SDSCA measure, were the most well-performed activities among all domains. Responses to inspection of the inside of shoes in the foot care activity (0.8±1.5) and specific exercise sessions in the exercise activity (1.6±1.9) reflected poor levels of compliance. According to the DSCB-OA questionnaire, the mean diabetes self-care barrier of DSCB-OA was 20.6±5.0 of total score 45. The greater perceived barriers to self-care on the DSCB-OA were having difficulty exercising regularly (1.9±0.7) and eating three meals and snacks leading to weight gain (1.9±0.8). Conclusion Young adults with early-onset diabetes showed a greater barrier to regular exercise and poor compliance with foot care and blood sugar testing. Healthcare providers must strengthen their relationship with young adults with diabetes to provide more education and guidelines for lifestyle modification focused on exercise and to promote higher compliance with diabetic self-care activities for improving clinical outcomes.