Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: Sclerostin, initially recognized for its pivotal role in bone metabolism, has gained attention for its multifaceted impact on overall human health. However, its influence on frailty—a condition that best reflects biological age—has not been thoroughly investigated. Methods: We collected blood samples from 244 older adults who underwent comprehensive geriatric assessments. Sclerostin levels were quantified using an enzyme-linked immunosorbent assay. Frailty was assessed using two validated approaches: the phenotypic model by Fried and the deficit accumulation frailty index (FI) by Rockwood. Results: After controlling for sex, age, and body mass index, we found that serum sclerostin levels were significantly elevated in frail individuals compared to their robust counterparts (P<0.001). There was a positive correlation between serum sclerostin concentrations and the FI (P<0.001). Each standard deviation increase in serum sclerostin was associated with an odds ratio of 1.87 for frailty (P=0.003). Moreover, participants in the highest quartile of sclerostin levels had a significantly higher FI and a 9.91-fold increased odds of frailty compared to those in the lowest quartile (P=0.003 and P=0.039, respectively). Conclusion These findings, which for the first time explore the association between circulating sclerostin levels and frailty, have significant clinical implications, positioning sclerostin as one of potential blood-based biomarkers for frailty that captures the comprehensive physical, mental, and social aspects of the elderly, extending beyond its traditional role in bone metabolism.

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.

Background: and Purpose We aimed to determine the proportion of Korean patients with early Alzheimer’s disease (AD) who are eligible to receive lecanemab based on the United States Appropriate Use Recommendations (US AUR), and also identify the barriers to this treatment. Methods: We retrospectively enrolled 6,132 patients with amnestic mild cognitive impairment or mild amnestic dementia at 13 hospitals from June 2023 to May 2024. Among them, 2,058 patients underwent amyloid positron emission tomography (PET) and 1,199 (58.3%) of these patients were amyloid-positive on PET. We excluded 732 patients who did not undergo brain magnetic resonance imaging between June 2023 and May 2024. Finally, 467 patients were included in the present study. Results: When applying the criteria of the US AUR, approximately 50% of patients with early AD were eligible to receive lecanemab treatment. Among the 467 included patients, 36.8% did not meet the inclusion criterion of a Mini-Mental State Examination (MMSE) score of ≥22. Conclusions Eligibility for lecanemab treatment was not restricted to Korean patients with early AD except for those with an MMSE score of ≥22. The MMSE criteria should therefore be reconsidered in areas with a higher proportion of older people, who tend to have lower levels of education.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study explores the experiences of practitioners involved in the Community Integrated Care for Individuals with Mental Illness pilot project in A City. The project integrates healthcare, housing, rehabilitation, and welfare services to support community integration and prevent rehospitalization. Methods: A qualitative descriptive study was conducted using focus group interviews with 12 practitioners with at least six months of experience in the project. Data was analyzed using content analysis based on Downe-Wamboldt's framework. Results: Four themes emerged: (1) Integration and Maintenance, (2) Change and Advancement, (3) Communication and Connection, and (4) Need and Challenge. The project improved service continuity, enhanced multidisciplinary collaboration, and increased professional efficacy. However, challenges such as resource limitations, policy constraints, and workforce shortages were identified. Conclusion The pilot project effectively supports mental health recovery and community integration. To ensure sustainability, service expansion, policy reinforcement, and workforce development are needed. Strengthening inter-agency collaboration and public awareness will further promote community-based mental health care.

Background: Children, adolescents, and young adults (CAYAs) with severe illnesses require intensive treatment, often relying on medical devices and advanced medical services.Modern medical technology has improved the lifespans of these patients. In addition, CAYAs represent a vulnerable group, resulting in a significant caregiving burden on the entire family.This study examined patterns of medical utilization following diagnosis of a life-limiting condition (LLC). Methods: We establish a cohort of 176,236 CAYAs who were first diagnosed with an LLC using National Health Insurance data between 2011 and 2013. Patients diagnosed with an LLC within the 3 years preceding this period and those who had died were excluded, and only those receiving care at a general medical hospital were included. In total, 25,410,411 claims for medical expenses, outpatient visits, and lengths of stay for medical utilization over the approximately 10 years up to 2020 were investigated (2.3% inpatients, 97.7% outpatients). Results: The average annual medical utilization per LLC patient among CAYAs following initial diagnosis included medical expenses of $1,163, 16.8 outpatient visits, and 18.7 days of admission. Among inpatients, cancer patients averaged $5,340 for total medical expenses and 21.0 days of admission, while non-cancer patients averaged $3,013 and 18.1 days, respectively. The overall average medical expenses during the first year following diagnosis of an LLC were $3,012, whereas for cancer patients they were $5,962. In addition, there was a sharp increase in total medical expenses as death approached, particularly in the last month of life, with a considerable proportion attributable to critical-care treatments. Conclusion Our investigation into medical utilization by CAYAs with an LLC in Korea provides a foundation for healthcare policy development. Timely treatment at each stage and tailored policies that take into account the heterogeneity among diseases are of paramount importance.

Background: This study analyzed the status of community-based practice in public healthcare institutions in Korean medical schools and identified related needs. Methods: We conducted an online cross-sectional survey in which 32 of 40 medical schools (80.0%) participated between March and April 2023. We developed questionnaire items aimed at ascertaining the status and perceptions of community-based practice and analyzed the response data using frequency analysis, the Mann-Whitney U test, and content analysis with word clouds. Results: Of the 32 medical schools analyzed, 23 (71.9%) offered practical courses, and of those, 12 (52.2%) implemented practice lessons within courses. Among 20 schools, 18 (90.0%) required students to complete practical courses and over 50% offered these courses in the third and fourth years of the clerkship phase. Perceptions of community practice showed no significant differences based on whether courses were offered. Many schools have proposed that practice should be a continuous curricular element from the premedical to medical years. The primary challenges facing community-based practice were identified as faculty development, collaboration, and compensation of practice institutions. The following words were extracted from the respondents’ comments: practice, community, institution, student, education, faculty, university, and public. Conclusion This study identified the limitations of community-based education provided by Korean medical schools and we report findings that highlight areas of improvement. Notable among these is the need to continuously incorporate community-based practice into medical education while engaging in discussions and conducting research toward developing a comprehensive and systematic curriculum.

Long coronavirus disease (COVID) is a condition in which coronavirus disease 2019 (COVID-19) symptoms persist for over 3 months, and currently poses a global public health challenge. Due to varying manifestations and lack of standardized definitions, diagnostic methods, and treatments, comprehensive clinical guidelines are required. This review article, summarizing research and expert consensus up to June 2023, provides recommendations for diagnosis and long-term management of long COVID symptoms. It emphasizes thorough patient evaluation, including medical history, physical examinations, and tests, and advocates vaccination and antiviral treatments to reduce risk. Guidelines for long COVID will be updated as new knowledge emerges.