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.

Rectal cancer, which accounts for approximately 40% of colorectal cancers, remains a major clinical concern. Recent advances in diagnostic imaging, surgical techniques, radiotherapy, and systemic treatment have steadily improved rectal cancer outcomes. Considering this, the Korean Rectal Cancer Multidisciplinary (KRCM) Committee has aimed to provide clinicians and policymakers with up-to-date, evidence-based clinical practice guidelines to support optimal decision-making, reflecting current evidence, the Korean healthcare context, and patient values and preferences. The Clinical Practice Guidelines for Rectal Cancer version 2.0 were developed through multidisciplinary collaboration with related academic societies, building upon and updating the KRCM Clinical Practice Guidelines version 1.0 (titled “Multidisciplinary guidelines for the management of rectal cancer”). These consensus guidelines of the KRCM were established based on a comprehensive literature review, evidence synthesis, with recommendation development guided by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology, and consideration of applicability in real-world clinical practice under the national health insurance system. Each recommendation has been presented with its strength and level of evidence.

Background: Copy number variations (CNVs) play an important role in human genetic disorders. Detection of exon-level CNVs is crucial for accurate clinical diagnosis. The CytoScan XON Array, a high-resolution microarray, was recently developed to detect exonic CNVs of various genes. Methods: We evaluated the clinical performance of the CytoScan XON Array using 59 patient samples with previously identified CNVs, confirmed via methods including multiple ligation-dependent probe amplification (MLPA), gene-dose PCR, and mRNA assay. Concordance between CytoScan XON and orthogonal methods was evaluated in target regions, and diagnostic utility was compared with that of genome sequencing (GS)-based CNV calling tools through analysis of false-positive CNVs in non-target genomic regions. Results: For target regions, the CytoScan XON Array achieved concordance rates of 89.8% and 92.5% at the exon and gene levels, respectively, for all CNV calls. Concordance was higher for multi-exon CNVs (100%) than that for single-exon CNVs (82.6%, P = 0.03). For non-target regions, false-positive CNV calls were reduced to fewer than 0.01 per gene per person through filtering strategies. The array exhibited false-positive detection rates within dosage-sensitive genes comparable with those of GS-based tools. Conclusions The CytoScan XON Array, a reliable tool for detecting exon-level CNVs in target regions, can serve as a complementary approach to GS-based CNV calling tools for genome-wide CNV screening with high resolution. However, its performance for single-exon CNVs requires further optimization. Cross-validation with GS-based CNV calling tools is recommended to improve diagnostic accuracy.

Background: Lithium hydroxide (LiOH) is increasingly used in electric vehicle battery production; however, its health effects in the work environment remain underreported. This study characterizes the acute health effects on workers following accidental occupational exposure to LiOH at a Korean lithium plant in March 2024. Methods: We analyzed health effects from two LiOH exposure accidents on March 6 and 9, 2024, involving 50–100 kg powder spills. Two datasets were examined: acute symptoms from 115 workers who visited hospitals immediately after exposure, and a symptom severity survey from 474 workers conducted 2 weeks post-exposure. Workers were stratified by distance from the leak source (<10 m, 10–20 m, >20 m) and respirator use. Univariate general linear modeling was applied to analyze the relationship between symptom occurrence and both the distance from the exposure source and respirator use. Results: Among workers visiting hospitals immediately, local irritation symptoms predominated: sore throat (58.3%), cough (28.7%), and skin dermatoses (17.4%). Systemic symptoms included headache (45.2%), nausea (18.3%), chest tightness (12.2%), and dizziness (9.6%). Two-week follow-up revealed overall symptom improvement; severe cough decreased from 22.2% to 10.1%. However, despite general improvement, a significant portion of workers reported persistent respiratory issues, including cough (28.7%) and sputum production (31.0%). Symptom severity showed a significant dose-response relationship with proximity to the source (p < 0.001). While respirator use offered initial protection (p = 0.021), this effect was not statistically significant after 2 weeks. Conclusions Occupational LiOH exposure caused acute irritation and systemic symptoms, demonstrating immediate tissue damage consistent with its alkalinity and systemic toxicity upon absorption. As lithium battery production expands globally, these results emphasize the necessity for developing specific occupational exposure limits and medical surveillance guidelines for lithium compounds.

Purpose: This study explored the experiences of physicians and nurses providing end-oflife care in Korean acute care hospitals. It aimed to identify the challenges faced in caring for dying patients and to suggest strategies for improving hospital-based end-of-life care. Methods: A qualitative exploratory design was employed using focus group interviews.Eleven healthcare professionals (five physicians and six nurses) working in tertiary or general hospitals participated in the study between July and August 2018. The interviews were conducted using a semi-structured guide covering seven thematic areas. All sessions were audio-recorded, transcribed verbatim, and analyzed thematically following Braun and Clarke’s framework. Results: Six major themes emerged: (1) communication with patients and families, (2) physical care for dying patients, (3) psychological and spiritual support, (4) hospital environment and system constraints, (5) moral distress and emotional burden on healthcare providers, and (6) suggestions for improvement. The participants described difficulties in open communication, limited resources for comfort care, emotional strain from invasive treatment at the end of life, and the absence of standardized institutional protocols.They emphasized the need for structured communication training, multidisciplinary collaboration, and integration of palliative care principles into acute care practice. Conclusion Physicians and nurses play a pivotal yet emotionally demanding role in providing end-oflife care in acute hospitals. Institutional reforms, including education, protocol development, and supportive environments, are essential to ensuring dignified, patient-centered care and sustain healthcare providers in their professional roles.

Osteoid osteoma accounts for approximately 10% of all benign bone tumors, but only approximately 4% of cases occur in the foot and ankle area. Periarticular osteoid osteoma frequently manifests with nonspecific clinical symptoms that mimic other conditions, potentially leading clinicians down a diagnostic side path and resulting in delayed or missed diagnoses compared to extra-articular osteoid osteoma. Although plain radiographs may show nonspecific findings, magnetic resonance imaging can detect bone marrow edema and surrounding soft tissue changes. Computed tomography is the most accurate modality for diagnosis. This paper reports the case of a 26-year-old female diagnosed with periarticular osteoid osteoma of the calcaneus and was treated with arthroscopic localized curettage at the author’s institution.

Older adults living alone face challenges in managing diabetes, yet research on glycemic control in this group is limited. This study analyzed data from the Korean National Health and Nutrition Examination Survey (2016~2021) to identify factors associated with glycemic control in 453 older adults with diabetes living alone. Methods: Glycemic control was categorized as good (glycated hemoglobin [HbA1c]<7.0%) or poor (HbA1c≥7.0%). Complex sample logistic regression examined demographic, disease and health-related, behavioral, and psychological factors associated with glycemic control. Results: Older adults aged ≥80 years had better glycemic control than those aged 65~69 years, while a diabetes duration of ≥15 years and higher body mass index were linked to poorer control. Strength training 5~7 days per week was associated with better control, whereas non-adherence to a healthy diet was unexpectedly linked to better outcomes. Conclusion: These findings highlight the need for tailored interventions to improve diabetes self-management and support healthy aging among older adults living alone. They also offer practical insights into shaping community-based health programs and social support systems for this population.

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.

Objective: To evaluate the diagnostic performance of the “probable hepatocellular carcinoma (HCC)” category in the Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) v2022 guidelines. Materials and Methods: This multicenter retrospective study included patients at risk of HCC who underwent gadoxetic acid-enhanced MRI between January 2015 and June 2018; a subgroup of these patients also underwent liver CT. Eligible patients had at least one non-cystic lesion (≥10 mm) with a reference standard. Four radiologists interpreted the images independently and the results were pooled. The performance of “definite HCC” and “probable HCC” together and “probable HCC” alone were compared between v2018 and v2022. Results: A total of 2,237 patients (1,666 men; mean age, 59 ± 11 years) with 2,445 lesions were included. In v2022, 1.5% (143/9,780) of the lesions were additionally categorized as “probable HCC” by four reviewers on MRI; among these, 104 lesions were not HCCs. Focal nodular hyperplasia (FNH) or FNH-like nodules constituted 90.4% (94/104) of the false positives. When “definite HCC” and “probable HCC” were combined, v2022 showed higher sensitivity (83.7% [5,670/6,776] vs. 83.1% [5,631/6,776]) but lower specificity (77.1% [2,316/3,004] vs. 80.6% [2,420/3,004]) than v2018 (P < 0.001). For “probable HCC” alone, v2022 showed a lower positive predictive value (PPV) than v2018 (64.1% [373/582] vs. 76.1% [334/439], P < 0.001). In v2022, lesions with non-rim arterial-phase hyperenhancement (APHE) showed a lower PPV than those without APHE (42.3% [91/215] vs. 76.8% [282/367], P < 0.001). In the CT subgroup (n = 1,590), 1.6% (99/6,360) of the lesions were reassessed as “probable HCC,” and its PPV was 83.8% (83/99) in v2022 whereas no lesions were classified as “probable HCC” under v2018. Conclusion The revised “probable HCC” category in the KLCA-NCC v2022 aligns with updates in the diagnostic flow, demonstrating acceptable performance on MRI and CT. Notably, FNH or FNH-like nodules can be misclassified as “probable HCC” when MRI is used.

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.