Objective: The association of lipid parameters with cardiovascular disease (CVD) and the impact of kidney function on this association have not been thoroughly evaluated in patients with type 2 diabetes mellitus (T2DM). Methods: Using the Korean National Health Insurance Service Cohort database, we identified 2,343,882 subjects with T2DM in 2015–2016. Baseline lipid levels and kidney function were evaluated and followed up until December 2020. Subjects were classified into three groups according to their estimated glomerular filtration rate (eGFR): ≥60, 30–59, or <30 mL/min/ 1.73 m2 . We analyzed the diabetes group with eGFR ≥60 and low-density lipoprotein cholesterol (LDL-C) <70 mg/dL as a reference group. Results: The risk of CVD began to increase at LDL-C ≥100 mg/dL in the eGFR ≥60 mL/min/m2group. The risk of CVD in the eGFR 30–59 mL/min/m2 group was increased by 43%, even in the LDL-C <70 mg/dL, and the risk increased progressively with LDL-C category. Among subjects with eGFR 30–59 mL/min/m2 , LDL-C 70–99, 100–129, 130–159, and ≥160 mg/ dL were significantly associated with the risk of CVD, with hazard ratio (95% confidence interval) of 1.48 (1.43–1.53), 1.54 (1.49–1.60), 1.55 (1.48–1.63), and 1.88 (1.77–2.00), respectively. In the eGFR <30 mL/min/m2 group, a 3.3-fold increased risk of CVD was seen, even at LDL-C <70 mg/dL. Conclusion The cutoff levels of LDL-C that increase CVD risk in patients with T2DM depend on kidney function, which influences the relationship between LDL-C and CVD risk in patients with T2DM.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Objective: As the demand for community mental health services continues to grow, the need for well-equipped and organized services has become apparent. This study aimed to optimize the roles and infrastructure of mental health services, by establishing, among other initiatives, standardized operating models. Methods: The study was conducted in multiple phases from May 12, 2021, to December 29, 2021. Stakeholders within South Korea and metropolitan mental health welfare centers were targeted, but addiction management support centers, including officials, patients, and their families, were integrated as well. A literature review and survey, focus group interviews, a Delphi survey, and expert consultation contributed to comprehensive revisions and improvements of the mental health service model. Results: The proposed model for community mental health welfare centers emphasizes the expansion of personnel and infrastructure, with a focus on severe mental illnesses and suicide prevention. The model for metropolitan mental health welfare centers delineates essential tasks in areas such as project planning and establishment, community research, and education about severe mental illnesses. The establishment of a 24-hour emergency intervention center was a crucial feature. In the integrated addiction support center model, the need to promote addiction management is defined as an essential task and the establishment of national governance for addiction policies is recommended. Conclusion This study proposed standard operating models for three types of mental health service centers. To meet the increasing need for community care, robust mental health service delivery systems are of primary importance.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

The prevalence of postpartum depression (PPD) in Asia is reported to range from 13.53% to 22.31%. However, there remains a gap in the identification of PPD, particularly regarding cultural cutoff points. Therefore, the purpose of this scoping review was to determine the prevalence and associated factors of PPD in Eastern, South-eastern, Western, and Southern Asian countries and analyze the cutoff points of the Edinburgh Postnatal Depression Scale (EPDS) used across these countries. Following Arksey and O'Malley’s five-step scoping review framework, the population was defined as mothers, the concept as the EPDS, and the context as the Asian region. A literature search was conducted using PubMed, Embase, CINAHL, PsycINFO, and Web of Science. The data analysis focused on demographic characteristics, EPDS cutoffs and features, PPD prevalence, and its associated factors. Nineteen studies were selected. Most countries used translated versions of the EPDS with demonstrated reliability and validity. The cutoff scores varied, with most using scores of 10 or higher. The prevalence of PPD ranged from 5.1% to 78.7%. Key associated factors for PPD included cultural factors such as relationships with in-laws and preferences for the newborn’s sex. To improve the accuracy of PPD screening in Asia, the EPDS should be used consistently, and appropriate cutoff criteria must be established. In addition, prevention strategies and programs that reflect the cultural characteristics and social context of Asia need to be developed for the early detection and prevention of PPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Background and Objectives: Among various emerging catheter-based treatments for severe tricuspid regurgitation (TR), the spacer device can reduce the regurgitation orifice without manipulating the valve leaflet. However, its clinical application has been hampered by traumatic anchoring to the myocardium and the coaxial alignment of the balloon resulting in insufficient TR reduction. This study aimed to evaluate the early-stage safety, technical feasibility, and preliminary efficacy of the novel atraumatic vertical spacer in patients with isolated severe TR. Methods: All procedures were guided by fluoroscopy and transthoracic echocardiography.The maximum device placement time with an inflated balloon was 24 hours. Changes in the amount of TR, right ventricular function, and patient hemodynamics were measured during balloon deployment. Results: A total of 7 patients (median age 74), underwent successful device implantation without procedure-related complications. During balloon inflation (median 25 minutes), there were no symptoms or signs indicative of TR intolerance. TR was reduced by 1 grade or greater in all patients, with 2 patients exhibiting a reduction of 3 grades, from torrential TR to a moderate degree. Mild TR after balloon inflation was achieved in 3 patients with baseline severe TR. The TR reduction observed during initial balloon deployment was sustained during the subsequent balloon maintenance period. Conclusions The Pivot-balloon procedure was safe, technically feasible, and effective in reducing TR in patients with severe TR. No periprocedural complications or adverse cardiovascular events were reported during device placement with TR reduction observed in all patients. However, longer-term follow-up is needed to confirm safety and treatment effect.

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.