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.

Background: and Purpose To compare the epidemiological and clinical features of the rare patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) with age- and sex-matched controls in a nationwide cohort from South Korea. Methods: This observational cohort study analyzed newly diagnosed CADASIL patients aged at least 20 years and matched controls using data from the National Health Information Database for 2004–2022. The cumulative incidence of CADASIL was assessed by age and sex, and compared between regions. Neurologic and systemic diseases were compared between the CADASIL and control groups. Results: The study analyzed 816 CADASIL patients and 816 age- and sex-matched controls aged 56.8±15.2 years (mean±standard deviation), among whom 48.3% were male. The cumulative incidence of CADASIL was 1.86 per 100,000 people (95% confidence interval [CI]=1.85– 1.87 per 100,000), and peaked at 60–69 years of age. In terms of regional distribution, the incidence was highest for Jeju, at 39.67 per 100,000 (95% CI 37.84–41.49 per 100,000). Neurologic diseases were more frequent in CADASIL patients, including Alzheimer’s disease (33.1% vs.20.0%), vascular dementia (84.9% vs. 5.0%), epilepsy (34.6% vs. 15.9%), stroke (70.7% vs. 27.6%), parkinsonism (18.9% vs. 11.0%), and depression (60.8% vs. 44.9%). Systemic diseases such as diabetes mellitus (78.9% vs. 68.9%) were also more common in CADASIL patients, while cancer (27.9% vs. 38.7%) and myocardial infarction (10.0% vs. 13.6%) were less common than in controls. The onset ages of all diseases were lower in CADASIL patients. Conclusions This study has provided a precise nationwide estimate of the CADASIL incidence and its regional distribution in South Korea. CADASIL patients showed higher incidence rates and earlier onsets of diverse clinical manifestations.

While South Korea’s National Health Insurance (NHI) was once disparaged as a rudimentary “discount program,” it has matured into the cornerstone of the nation’s medical safety net owing to sustained governmental initiatives. Nevertheless, the pursuit of expanded benefit coverage, exacerbated by demographic shifts toward low fertility and an aging society, has catalyzed a rapid escalation in aggregate national healthcare spending.Consequently, there is an urgent need for the NHI to implement benefit expansion policies that prioritize cost-efficiency and fiscal prudence. This perspective asserts that coverage enhancement should be strategically focused on high-cost catastrophic illnesses, specifically through the robust fortification of the annual out-of-pocket (OOP) maximum system. Furthermore, the reform of private health insurance is imperative, as its unbridled growth in non-reimbursable services has undermined the efficacy of public coverage efforts. This paper proposes concrete policy frameworks for both the enhancement of the OOP maximum system and the structural reform of private indemnity health insurance.

Background: A systematic evaluation of potential living liver donors is essential to ensure donor safety and optimize recipient outcomes in living donor liver transplantation (LDLT). This study aimed to assess donor acceptance rates and reasons for disqualification among individuals evaluated for LDLT at a high-volume transplant center over a one-year period. Methods: We retrospectively reviewed 1,087 potential living liver donors who presented for LDLT evaluation in 2023. Of these, 991 candidates advanced beyond the initial screening (Stage 1) and underwent comprehensive clinical, imaging, and pathological assessments (Stages 2 and 3). Candidates who discontinued after Stage 1 were excluded due to the absence of documented reasons for non-progression. Results: Among the 991 candidates who proceeded beyond initial screening, 473 (47.7%) completed the full donor evaluation, of whom 466 were judged to be suitable donors. Among suitable donors, 384 (82.4%) proceeded to donor hepatectomy, whereas 82 did not, primarily due to recipient-related factors such as clinical deterioration or withdrawal of consent. Donor ineligibility was determined in 422 candidates (42.6%), most commonly due to inadequate remnant liver volume (52.8%), hepatic steatosis (20.6%), and insufficient graft size (10.2%). Among candidates undergoing Stage 2 evaluation, 162 (16.3%) failed to meet steatosis criteria; 126 were excluded solely for steatosis and advised weight reduction, and 39 subsequently became eligible and successfully donated. Conclusion In this high-volume LDLT center, donor disqualification was primarily driven by remnant liver volume and hepatic steatosis. Targeted interventions such as weight reduction enabled successful donation in a subset of initially ineligible candidates, underscoring the importance of individualized donor evaluation and pre-donation optimization.

Robotic thyroidectomy has progressed from multiport to single-port (SP) platforms to minimize invasiveness and improve cosmesis. The da Vinci SP system (Intuitive Surgical) combines a flexible 3-dimensional endoscope with 3 wristed instruments in a single 2.5-cm cannula-enabled concealed remote access route and mitigates external arm collisions.This review synthesized PubMed-indexed reports (2020–2025) on SP robotic thyroidectomy using the following approaches:transaxillary variants, SP areolar, retroauricular/facelift (SP-hairline variants), and transoral approach. We focused on technical refinement, learning curves, and clinical outcomes. We highlight technical refinements and clinical outcomes across access routes. Contemporary series indicate that SP thyroidectomy is feasible and safe in well-selected patients, with high cosmetic satisfaction and operative metrics comparable to those of multiport cohorts. Among the SP routes, transaxillary variants have the most mature peer-reviewed reporting and are therefore discussed in greater detail. Early applications of SP-assisted lateral neck dissection have also been described. The limitations of current SP platforms include constrained counter-traction, reduced internal workspace, and incomplete integration of advanced energy devices.Nonetheless, ongoing device innovations and the growing global experience suggest that SP systems will increasingly shape endocrine neck surgeries.

Atopic dermatitis is the most common chronic inflammatory skin disease in children and adolescents. The Korean Academy of Pediatric Allergy and Respiratory Disease published the Atopic Dermatitis Treatment Guideline in 2008, which has been helpful in atopic dermatitis treatment until now. Various reports on the development and effectiveness of new drugs have suggested that there is a need to develop and revise old treatment guidelines. Part 1 aimed to provide evidence-based recommendations for skin care management and topical treatment for atopic dermatitis. Part 2 focuses on systemic treatment, novel therapeutics, and adjuvant therapy. The goal of this guideline is intended to assist front-line doctors treating pediatric and adolescent atopic dermatitis patients make safer, more effective, and more rational decisions regarding systemic treatment, novel therapeutics, and adjuvant therapy by providing evidence-based recommendations with a clear level of evidence and benefit regarding treatment.

Atopic dermatitis is the most common chronic inflammatory skin disease in children and adolescents. The Korean Academy of Pediatric Allergy and Respiratory Disease published the Atopic Dermatitis Treatment Guideline in 2008, which has been helpful in atopic dermatitis treatment until now. Various reports on the development and effectiveness of new drugs have suggested that there is a need to develop and revise old treatment guidelines. Part 1 aimed to provide evidence-based recommendations for skin care management and topical treatment for atopic dermatitis. Part 2 focuses on systemic treatment, novel therapeutics, and adjuvant therapy. The goal of this guideline is intended to assist front-line doctors treating pediatric and adolescent atopic dermatitis patients make safer, more effective, and more rational decisions regarding systemic treatment, novel therapeutics, and adjuvant therapy by providing evidence-based recommendations with a clear level of evidence and benefit regarding treatment.

Purpose: The purpose of this study was to develop an approach to alleviate the discomfort caused by sandbag compression after a bone marrow examination. This research examined the effects of applying a pressure hemostasis band on bleeding, pain, and discomfort at the bone marrow examination site. Methods: This study was conducted with a nonequivalent control group non-synchronized design. For 74 patients under evaluation who underwent bone marrow examination, sandbag compression was applied to the examination site in the control group (n=37), and a pressure hemostasis band was applied to the intervention group (n=37). In both groups, absolute bed rest was performed for two hours, and bleeding, pain, and discomfort at the examination site were measured. Results: After two hours of the bone marrow examination, there was no difference in bleeding on the gauze between the two groups (F=0.59, p=.444). Bleeding occurred in three patients in the intervention group and six in the control group (χ 2 =1.14, p=.479), with no cases of hematoma detected in either group. One hour post-examination, the control group experienced significantly higher pain (F=5.45, p=.022) and discomfort (F=5.68, p=.020) than the intervention group. However, pain and discomfort levels were similar between groups after two hours. Conclusion Compared to the sandbag compression group, the band application group showed no difference in bleeding and experienced less pain and discomfort at the examination site. This confirms that the pressure hemostasis band is a suitable alternative to sandbag compression in post-examination care.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.