Background: s/Aims: Phase angle (PhA), as measured by bioelectrical impedance analysis, provides insights into hydration and nutritional status, making it a prognostic indicator of frailty. While low preoperative PhA has been linked to postoperative complications in cancer patients, its predictive value in individuals undergoing pancreaticoduodenectomy (PD) has not been thoroughly investigated.This study aims to evaluate the clinical utility of preoperative PhA in predicting postoperative complications for patients undergoing PD. Methods: Among 41 patients who underwent PD at Seoul National University Hospital between September and December 2024, 35 were included in the analysis after excluding 6 patients who had concomitant blood vessel or other organ resections. Patients were divided into low (Comprehensive Complication Index [CCI] ≤ 20) and high (CCI > 20) complication groups based on the CCI, derived from the Clavien–Dindo classification. The differences in PhA between the two groups were analyzed, and logistic regression was performed to assess the relationship between PhA and CCI. Results: The mean PhA was significantly lower in the high-CCI group compared to the low-CCI group (5.7° vs. 6.7°, p = 0.025). Multivariate logistic regression analysis indicated that PhA (odds ratio: 0.17; 95% confidence interval: 0.04–0.68; p = 0.012) was an independent predictor of high CCI. A low preoperative PhA was associated with an increased risk of postoperative complications following PD. Conclusions Preoperative PhA may serve as a valuable predictive indicator of postoperative complications after PD, enabling the identification of patients who could benefit from preoperative prehabilitation, including nutritional support.

Background: Precision oncology is advancing, increasing the demand for comprehensive, non-invasive genomic profiling tools. Liquid biopsy using circulating tumor DNA (ctDNA) enables real-time molecular profiling, treatment monitoring, and early detection of resistance variants. We developed the PAN100 panel (Dxome), a hybridization capture panel targeting 101 genes, as a pan-cancer genotyping assay to detect clinically actionable variants across various cancer types. This study presents the first comprehensive validation of the PAN100 panel including both analytical and clinical performance across eight cancer types using reference materials and matched tissue samples. Methods: For analytical validation, we assessed accuracy, limit of detection (LoD), and precision using Seraseq ctDNA v2 Reference Materials (SeraCare, Milford, MA, USA). Clinical validation was performed using plasma samples from 27 patients with eight types of cancer and 17 matched tumor samples. Positive percent agreement (PPA) between ctDNA and tissue next-generation sequencing (NGS) results was assessed using TruSight Oncology 500 and TruSight Tumor 170 assays. The limit of blank (LoB) was evaluated in 34 healthy individuals. Results: The PAN100 panel demonstrated high precision and linearity (LoD, 0.3%; 95.0% confidence interval, 0.29–0.35) variant allele frequency. The PPA between ctDNA and tissue NGS was 73.1% for single-nucleotide variants, 80.0% for insertions/deletions, and 74.2% overall. The LoB was 0.00001%. Conclusions The PAN100 panel is a robust tool for detecting clinically significant variants with high concordance with tissue NGS. Its sensitivity for low-frequency variants enables real-time treatment adaptation, supporting precision oncology. Its comprehensive design is particularly valuable for challenging diagnoses and clonal evolution monitoring.

Purpose: We aimed to compare the final adult height (FAH) of male patients with central precocious puberty (CPP) after treatment with a gonadotropin-releasing hormone agonist (GnRHa). Specifically, we compared FAH with the target height (TH) and the predicted adult height (PAH) before and after GnRHa treatment to quantify height gain and identify predictive factors. Methods: We retrospectively reviewed the medical records of 92 male patients with CPP and known FAH after GnRHa treatment at the Department of Pediatrics of Severance Children’s Hospital between January 2000 and June 2024. Results: The mean duration of GnRHa treatment was 2.7±1.3 years. A significant 1.1±0.9 years narrowing was observed in the difference between bone age (BA) and chronological age (CA) during treatment (P<0.001). TH was 172.4±3.4 cm. FAH was 173.6±6.4 cm. FAH was greater than TH by 1.2±5.9 cm (P=0.047). PAH before and after treatment was 179.9±8.1 and 181.2±7.4 cm, respectively. PAH was increased by 1.3±4.9 cm (P=0.012) after treatment. As the PAH standard deviation score (SDS) before GnRHa treatment increased, FAH tended to exceed TH. In contrast, higher testosterone levels before treatment are associated with FAH falling below TH. A longer duration of treatment and taller TH are associated with an FAH SDS greater than height SDS before treatment. Conversely, a greater weight SDS, BA–CA difference, and testis size before treatment are associated with FAH SDS being less than height SDS before GnRHa treatment. Conclusion GnRHa treatment improved FAH and inhibited bone maturation in male patients with CPP.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Background: Despite advancements in laboratory animal facility management, pinworm infections remain a persistent issue in immunodeficient mouse colonies. Rapid diagnosis and treatment are crucial to mitigating potential scientific and economic consequences. Effective control requires both the administration of anthelmintic agents and rigorous environmental decontamination. However, the safety and efficacy of these treatments in genetically modified mouse models remains uncertain.Case presentation Aspiculuris tetraptera infestation was identified in multiple immunodeficient mouse models housed in a laboratory facility. Diagnosis was confirmed through fecal flotation for egg detection and necropsy for adult worm examination in the large intestines. Mice received three subcutaneous ivermectin injections at two-week intervals, coupled with environmental decontamination using ivermectin spray for four consecutive weeks. Following treatment, all colonies tested negative for A. tetraptera without any mortality. Conclusions A combination of subcutaneous ivermectin injection and environmental spray application effectively eradicated A. tetraptera infestation in immunodeficient mouse colonies. The treatment protocol led to the complete elimination of eggs and adult worms, offering a practical strategy for managing pinworm infections in genetically modified mouse models. Limitations include the small sample size, and the lack of a comprehensive evaluation of physiological and metabolic safety in immunodeficient mice. Further validation will be required to confirm the broader applicability of this approach.

Purpose: The current study provides national cancer statistics and their secular trends in Korea, including incidence, mortality, survival, and prevalence in 2023, with international comparisons. Materials and Methods: Cancer incidence, survival, and prevalence rates were calculated using the Korea National Cancer Incidence Database (1999-2023), with survival follow-up until December 31, 2024. Mortality data were obtained from the Ministry of Data and Statistics, while international comparisons were based on GLOBOCAN data. Results: In 2023, 288,613 newly diagnosed cancer cases (age-standardized rate [ASR], 288.6 per 100,000) and 85,271 deaths from cancer (ASR, 64.3 per 100,000) were reported. Among the incident cases, 145,452 (50.4%) were aged 65 years or older. Prostate cancer became the most common cancer among men for the first time. The proportion of localized-stage cancers increased from 45.6% in 2005 to 51.8% in 2023. Korea had the lowest cancer mortality among countries with similar incidence rates and the lowest mortality-to-incidence ratios for stomach, colorectal, and breast cancer. The 5-year relative survival rate (2019-2023) was 73.7% overall and 92.7% for localized-stage cancers. Over 2.73 million prevalent cases were identified in 2023, representing 5.3% of the Korean population. Conclusion These findings indicate that Korea’s cancer control efforts have contributed to early detection and improved survival outcomes. As Korea enters a super-aged society in 2025, cancer burden will continue to increase, requiring sustained and adaptive cancer control strategies.

Purpose: Older cancer patients face unique challenges due to age-related physiological changes, increasing their vulnerability to treatment-related toxicities. Geriatric assessment (GA) is a validated tool for optimizing care, yet there is no consensus on integrating geriatric interventions into oncology. This study evaluates the feasibility of a tailored onco-geriatric intervention model incorporating the KG-7 screening tool. Materials and Methods: This prospective study included 30 patients aged ≥ 70 years with solid tumors undergoing adjuvant or palliative chemotherapy. Patients scoring ≤ 5 of KG-7 were eligible. Tailored interventions incorporating KG-7 included polypharmacy, functional status, mobility, nutrition, cognition, emotional well-being, insomnia, social support, and medical problem. KG-7, GA, and quality of life (QoL) were followed at 12 weeks. Results: Participants (median age, 79.5 years) had colon (43.3%), pancreatic (23.3%), or gastric cancer (23.3%). At baseline, most patients showed independent activities of daily living (100%)/instrumental activities of daily living (90%). However, 93.3% had abnormal GA. Particularly, 86.7% were either malnourished or at risk of malnutrition. The most frequently identified intervention needs included polypharmacy (70.0%), nutritional support (60.0%), and emotional well-being (50.0%) with high adherence (100.0%, 88.9%, and 46.7%, respectively). At 12 weeks, KG-7 scores improved in 43.8% of patients, and 69.2% of GA domains were improved. QoL analysis revealed modest improvement in Global Health Status (mean difference, 6.3; p=0.176). One-year survival rates were 92.3% and 79.4% for adjuvant and palliative groups, respectively. Conclusion The onco-geriatric intervention model incorporating KG-7 demonstrated high feasibility and potential to enhance clinical outcomes. Future studies should validate this approach in randomized trials to optimize care for older cancer patients.

Chronic kidney disease (CKD) is a progressive condition characterized by declining kidney function principally driven by diabetes mellitus, glomerulonephritis, and hypertension. Although renal biopsy is the gold standard for diagnosing CKD, its invasive nature restricts its use for early detection and routine clinical applications. Current noninvasive biomarkers, including the estimated glomerular filtration rate and albumin-to-creatinine ratio, are useful indicators of kidney dysfunction but fall short in specificity and sensitivity required to distinguish between CKD subtypes, including diabetic kidney disease and glomerulonephritis. Recently, urinary extracellular vesicles (uEVs), nano-sized lipid bilayer entities ranging from 30 to 1,000 nm in diameter and secreted by renal cells, have emerged as promising biomarkers for CKD. uEVs encapsulate a diverse array of proteins, nucleic acids, and lipids that mirror kidney pathophysiology, presenting a noninvasive means to assess disease progression, inflammation, fibrosis, and oxidative stress within the urinary system. Furthermore, uEVs offer a molecular fingerprint of kidney health, positioning them as potential tools for precision medicine. This review explores the diagnostic potential of uEVs, underscoring the need for standardization in urine collection, normalization techniques, and uEV isolation methodologies. We also highlight uEV-based biomarkers that distinguish various CKD subtypes and mirror pathological changes within the kidneys and urogenital system. As molecular proxies of their cells of origin, uEVs hold significant promise in enhancing CKD diagnostics to enable early detection, disease classification, and the development of novel therapeutic strategies.

Background/Aims: Despite numerous global changes in Helicobacter pylori treatment guidelines over the past decade, no comprehensive nationwide trend analysis has been conducted.We aimed to investigate the annual trends in the use of H. pylori treatment regimens on the basis of hospital type and region to identify whether changes in prescription patterns aligned with the Korean guidelines updated in 2013 and 2020. Methods: Using data from Korean Health Insurance Review and Assessment database spanning from January 2010 to December 2022, we extracted the performance code for H. pylori diagnosis along with the drug combination code for H. pylori treatment. Results: We analyzed the annual trends in standard triple therapy (STT; n=664,748), bismuth quadruple therapy (BQT; n=151,828), concomitant therapy (CT; n=3,034), sequential therapy (SEQ; n=1,612), and salvage treatment. Overall, STT use declined, with the use of 7-day STT decreasing but the use of 10- and 14-day STT increasing. The use of BQT as a first-line treatment consistently increased, and non-BQT (i.e., CT and SEQ) use also increased sharply since 2019.The tendency to adhere to the guideline changes was more pronounced in primary care clinics.Salvage treatment with BQT after STT failure exhibited a declining trend from 2010 to 2017, followed by an increase since 2018. Salvage treatment with levofloxacin triple therapy after BQT failure increased over time. Conclusions This long-term nationwide trend analysis revealed that real-world prescriptions for H. pylori treatment generally corresponded to the updated guidelines. Efforts are needed to disseminate the revised guidelines to achieve higher compliance rates.

Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.