Background: Preclinical studies have reported anticancer properties of sodium-glucose cotransporter 2 inhibitors (SGLT2is). We aimed to elucidate the association between the use of SGLT2is and the risk of prostate cancer among male patients with type 2 diabetes mellitus (T2DM). Methods: An active-comparator, new-user cohort design using a nationwide database between September 2014 and June 2020 was conducted on 45,601 new SGLT2i users and 205,395 new users of other glucose-lowering medications (oGLMs). In the following 1:1 propensity score matched (PSM) analysis, 35,371 SGLT2i users matched with an equivalent number of oGLM users were assessed. The hazard ratios (HRs) and 95% confidence intervals (CIs) for prostate cancer were calculated. Results: Among the cohort, prostate cancer was diagnosed in 210 out of 45,601 SGLT2i users, corresponding to a cumulative incidence of 1.0%, in contrast to 1,880 cases among 205,395 users of oGLMs, with a cumulative incidence of 1.5%. The use of SGLT2is was significantly correlated with a reduced risk of prostate cancer based on a multivariable-adjusted HR of 0.83 (95% CI, 0.71 to 0.98). PSM analysis affirmed 18% reduction in prostate cancer risk associated with SGLT2i use (HR, 0.82; 95% CI, 0.67 to 0.99). Subgroup analyses revealed that body mass index (BMI) significantly influenced the effect of SGLT2i on prostate cancer risk, with a more pronounced reduction in the subgroup with a BMI <25 kg/m2 (P=0.037). Conclusion The use of SGLT2is in Korean male patients with T2DM is associated with a lower risk of prostate cancer.

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.

Neuropathic pain markedly impairs quality of life and imposes a substantial socioeconomic burden, while available treatments often provide only partial relief and are limited by safety concerns. The Neuropathic Pain Special Interest Group of the International Association for the Study of Pain (NeuPSIG-IASP) first published pharmacologic recommendations in 2007, followed by a major update in 2015 and a new guideline in 2025. This narrative review specifically compares the 2015 and 2025 NeuPSIG-IASP guidelines, outlining key methodological changes and therapeutic shifts. The 2025 guideline is based on a larger, more rigorous meta-analysis, maintains α2δ-ligands (adds mirogabalin), serotonin-noradrenaline reuptake inhibitors, and tricyclic antidepressants as first-line drugs, downgrades tramadol into the opioid third-line group. It also introduces high-frequency motor-cortex repetitive transcranial magnetic stimulation as a weakly recommended third-line option and discusses implications for Korean clinical practice.

Background: Renal function declines with age as the kidneys become more vulnerable to inflammation and cellular senescence. This study examined gene expression changes linked to renal aging and assessed whether short-term calorie restriction (CR), a known anti-aging intervention, could reverse these alterations. Methods: Using RNA-seq data, we applied bioinformatics, systems biology, and molecular biology approaches to identify differentially expressed genes during aging and under CR. Gene Ontology and pathway analyses revealed that both aging and CR altered the expression of key senescence-associated secretory phenotype (SASP) genes, including cytokines and chemokines (Il1b, Ccl3, Ccl5, Il19, and Il24) and growth factors (Timp1 and Mmp12). Results: Renal aging is also associated with an increased expression of cell cycle arrest markers (p15INK4B (Cdkn2b), p16INK4A (Cdkn2a), and p21 (Cdkn1a)), which are suppressed by CR, suggesting a link to cellular senescence. Quantitative analysis of renal tissue samples confirmed the age-associated upregulation of these genes at the transcriptional level, and CR effectively attenuated these changes. Among these genes, we focused on the members of the interleukin 20 (IL-20) family, particularly Il19 and Il24. Furthermore, experimental induction of cellular senescence using H2O2 resulted in elevated Il19 and Il24 expression alongside other senescence markers. These findings suggest that aging and short-term CR regulate the IL-20 family expression, potentially influencing cellular senescence. Conclusion Our study suggests that Il19 and Il24 are associated with age-related renal decline and may represent hypothesis-generating candidates, highlighting potential molecular targets for future mechanistic and therapeutic investigations.

Background: Current guidelines recommend factor IIa- or Xa-specific inhibitors over warfarin analogs for preventing thromboembolic stroke in patients with atrial fibrillation (AF).However, their plasma concentrations in Korean patients are not well understood. Methods: We conducted a single-center laboratory study to determine the distribution ranges of peak and trough concentrations of three factor Xa inhibitors (apixaban, edoxaban, and rivaroxaban) prescribed for preventing strokes in patients with AF. Patients receiving one of these drugs and undergoing blood specimen collection for laboratory tests were screened. Blood specimens were obtained from patients who had adhered to the prescribed drug regimen consistently for at least 1 week. Drug plasma concentrations were measured using heparin liquid-reagent technology-based anti-Xa chromogenic assays. Results: We selected 459 patients who were taking standard or on-label-reduced doses of apixaban (N = 252), edoxaban (N = 182), or rivaroxaban (N = 25). The 5th–95th percentile ranges of the peak concentrations were 84–414 ng/mL (apixaban), 72–424 ng/mL (edoxaban), and 97–517 ng/mL (rivaroxaban). The respective 5th–95th percentile ranges of the trough concentrations were 44–237 ng/mL, 23–93 ng/mL, and 13–219 ng/mL. Approximately 19.6% (apixaban), 33.3% (edoxaban), and 64.0% (rivaroxaban) of patients in each group had peak concentrations out of the predicted distribution ranges based on pharmacokinetic data. Approximately 7.3%, 52.8%, and 8.3% of patients had trough concentrations out of the predicted distribution ranges. Conclusions A considerable proportion of Korean patients with AF taking factor Xa inhibitors may require population-specific reference ranges to guide therapeutic monitoring.

Flow cytometric lymphocyte subset analysis (FCLSA) is essential for assessing immune status across various diseases and clinical settings. We surveyed current clinical laboratory practices related to FCLSA to establish a baseline reference for future standardization in Korea. Nine university hospitals actively performing FCLSA responded to the 22-question survey, which covered seven categories of laboratory practice. These hospitals used commercial reagent antibody kits from either Beckton Dickinson Biosciences (N = 4) or Beckman Coulter Diagnostics (N = 5). Most hospitals performed daily instrument setup and scheduled maintenance every 2–6 months. Two levels of commercial quality control materials were routinely used each day. Sample and reagent antibody volumes varied across hospitals, even when the same reagent kit was used. Acquired cell counts ranged from 5 × 10 3 to 5 × 10 4 cells, with two hospitals adjusting counts based on the cell type analyzed. Most laboratories reported percentages and general opinions; some additionally reported white blood cell and lymphocyte counts, along with lymphocyte percentages. This is the first comprehensive survey on the clinical laboratory practice of FCLSA in Korea.Standardization of FCLSA should be accelerated to ensure reliable and reproducible results.

Background: Long working hours have been associated with adverse physical and mental health outcomes; however, evidence regarding their relationship with satisfaction with work environment remains limited, particularly when long working hours are defined using a specific daily threshold. This study examined the association between working ≥10 hours per day and satisfaction with work environment among Korean wage workers, focusing on the cumulative number of such workdays per month. Methods: This cross-sectional study analyzed data from the 7th Korean Working Conditions Survey. A total of 24,269 wage workers aged ≥18 years were included after excluding self-employed workers, unpaid family workers, shift workers, and respondents with missing data. Working ≥10 hours per day was categorized as 0, 1–9, and ≥10 days per month. Satisfaction with work environment was categorized as satisfied or dissatisfied. Multiple logistic regression analyses were conducted to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for dissatisfaction with work environment according to the number of long working days, adjusting for demographic and occupational characteristics. Results: Compared with workers who did not work ≥10 hours per day, those who worked 1–9 days and ≥10 days per month showed progressively higher levels of dissatisfaction with work environment. After adjustment for demographic and occupational factors, the odds of dissatisfaction with work environment were significantly higher among workers who worked ≥10 hours per day for 1–9 days per month (OR: 1.380; 95% CI: 1.145–1.665) and ≥10 days per month (OR: 2.106; 95% CI: 1.627–2.725), demonstrating a dose–response relationship. Conclusions Among the analytic sample of Korean wage workers included in this study, working ≥10 hours per day was associated with greater dissatisfaction with work environment, with a dose–response pattern according to the number of long working days per month.

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.

Myopia, particularly high myopia, is a significant risk factor for several ocular pathologies including cataract, glaucoma, and retinal detachment. Excessive axial elongation associated with high myopia can induce biomechanical stretching, increasing the risk of serious complications like posterior staphyloma and myopic maculopathy. Global meta-analyses estimate that approximately 10 million people were visually impaired due to myopic maculopathy in 2015, with 3 million being blind. Recent nationwide surveys in South Korea revealed a prevalence of 65.4% for myopia and 6.9% for high myopia in children and adolescents, highlighting the urgent need for effective management. Delaying the onset and slowing the progression of myopia during childhood and adolescence is crucial for reducing the potential lifetime risk of these complications. This consensus statement, prepared by the Korean Myopia Society for the Korean Association for Pediatric Ophthalmology and Strabismus (KAPOS), reviews the current evidence for myopia control interventions and provides management strategies applicable to the South Korean clinical setting. Key interventions covered include lifestyle modifications (outdoor time, near work adjustment), optical methods (myopia-control spectacle lenses, dual-focus soft contact lenses, orthokeratology), and pharmacologic treatment (low-concentration atropine), as well as combination therapies. The statement also addresses patient selection, treatment outcome evaluation using spherical equivalent and axial length changes, and the crucial aspects related to treatment cessation and the rebound effect.

The global increase in obesity highlights the need for accurate tools to assess body composition and monitor treatment efficacy.Traditional metrics, including body mass index and waist circumference, offer limited precision for fat quantification. Imagingbased techniques capable of visualizing internal structures are increasingly being recognized for their ability to provide comprehensive fat assessment. This review outlines the principles, strengths, and limitations of key modalities, including dualenergy X-ray absorptiometry (DXA), CT, MRI, and bioelectrical impedance analysis (BIA). DXA is cost-effective and accessible for population-level screening, whereas CT and MRI offer higher precision, particularly for visceral fat assessment. BIA is a practical, low-cost alternative, but it is limited by variability and lack of standardization. Regulatory agencies, including the US Food and Drug Administration and the Korean Ministry of Food and Drug Safety, are increasingly supporting imaging-based endpoints in clinical trials of anti-obesity drugs because these methods capture fat mass reduction beyond total weight loss. Recent phase III trials of semaglutide and tirzepatide have underscored the utility of DXA and CT in quantifying fat loss and preserving lean mass. Selecting appropriate imaging modalities based on technical capabilities and regulatory considerations can improve the evaluation of obesity treatments and strengthen the design of anti-obesity drug trials.