Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

This guideline outlines the use of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for the diagnosis and management of neuroendocrine tumors, brain tumors, and other tumorous conditions. It provides detailed recommendations on patient preparation, imaging procedures, and result interpretation. Based on inter-national standards and adapted to local clinical practices, the guideline emphasizes safety, quality control, and the effec-tive application of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for various tumors such as insulinomas, pheochromocytomas, and medullary thyroid carcinoma. It also addresses the use of premedication with carbidopa, fasting protocols, and optimal imaging techniques. The aim is to assist nuclear medicine professionals in delivering precise diagnoses, improving patient outcomes, and accommodating evolving medical knowl-edge and technology. This comprehensive document serves as a practical resource to enhance the accuracy, quality, and safety of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography in oncology.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

This review examines the challenges associated with occupational disease surveillance in Korea, particularly emphasizing the limitations of current data sources such as the Industrial Accident Compensation Insurance (IACI) statistics and special health examinations. The IACI system undercounts cases due to its emphasis on severe diseases and restrictions on approvals. Special health examinations, although they cover a broad workforce, are constrained by their annual scheduling, which leads to missed acute illnesses and subclinical conditions. The paper also explores the history of occupational disease surveillance in Korea, highlighting the fragmented and disease-specific approach of earlier systems. The authors introduce the newly established Korea Occupational Disease Surveillance Center (KODSC), a comprehensive nationwide system designed to gather, analyze, and interpret data on occupational diseases through a network of regional centers. By incorporating hospital-based surveillance and focusing on acute poisonings and other sentinel events, the KODSC aims to overcome the limitations of previous systems and promote collaboration with various agencies. Although it is still in the early stages of implementation, the KODSC demonstrates potential for improving data accuracy and contributing valuable insights for public health policy.

Background: Malnutrition exacerbates the prognosis of numerous diseases; however, its specific impact on severe coronavirus disease 2019 (COVID-19) outcomes remains insufficiently explored. Methods: This multicenter study in Korea evaluated the nutritional status of 1,088 adults with severe COVID-19 using the Geriatric Nutritional Risk Index (GNRI) based on serum albumin levels and body weight. The patients were categorized into two groups: GNRI >98 (no-risk) and GNRI ≤98 (risk). Propensity score matching, adjusted for demographic and clinical variables, was conducted. Results: Of the 1,088 patients, 642 (59%) were classified as at risk of malnutrition. Propensity score matching revealed significant disparities in hospital (34.3% vs. 19.4%, p<0.001) and intensive care unit (ICU) mortality (31.5% vs. 18.9%, p<0.001) between the groups. The risk group was associated with a higher hospital mortality rate in the multivariate Cox regression analyses following propensity score adjustment (hazard ratio [HR], 1.64; p=0.001). Among the 670 elderly patients, 450 were at risk of malnutrition. Furthermore, the risk group demonstrated significantly higher hospital (52.1% vs. 29.5%, p<0.001) and ICU mortality rates (47.2% vs. 29.1%, p<0.001). The risk group was significantly associated with increased hospital mortality rates in the multivariate analyses following propensity score adjustment (HR, 1.66; p=0.001). Conclusion Malnutrition, as indicated by a low GNRI, was associated with increased mortality in patients with severe COVID-19. This effect was also observed in the elderly population. These findings underscore the critical importance of nutritional assessment and effective interventions for patients with severe COVID-19.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

This guideline outlines the use of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for the diagnosis and management of neuroendocrine tumors, brain tumors, and other tumorous conditions. It provides detailed recommendations on patient preparation, imaging procedures, and result interpretation. Based on inter-national standards and adapted to local clinical practices, the guideline emphasizes safety, quality control, and the effec-tive application of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for various tumors such as insulinomas, pheochromocytomas, and medullary thyroid carcinoma. It also addresses the use of premedication with carbidopa, fasting protocols, and optimal imaging techniques. The aim is to assist nuclear medicine professionals in delivering precise diagnoses, improving patient outcomes, and accommodating evolving medical knowl-edge and technology. This comprehensive document serves as a practical resource to enhance the accuracy, quality, and safety of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography in oncology.