Nam Gi Hong

Although elevated serum gamma-glutamyl transferase activity (GGT) has been linked with metabolic risk factors for sarcopenia, including non-alcoholic fatty liver disease, adiposity, and insulin resistance, whether GGT independently associated with sarcopenia and sarcopenic obesity has not yet been investigated. We analyzed cross-sectional data of 3,193 community-dwelling adults (42.2% men, age 63.4 ± 8.7) aged ≥50 years from the Fifth Korean National Health and Nutrition Examination Survey, 2010

Osteoporosis and vertebral fractures (VFs) remain underdiagnosed. The addition of deep learning methods to lateral spine radiography (a simple, widely available, low-cost test) can potentially solve this problem. In this study, we develop deep learning scores to detect osteoporosis and VF based on lateral spine radiography and investigate whether their use can improve referral of high-risk individuals to bone-density testing. The derivation cohort consisted of patients aged 50 years or older who

CONTEXT: Teriparatide (TPTD) therapy has been proposed as a potential treatment strategy in severe cases of pregnancy- and lactation-associated osteoporosis (PLO) characterized by the occurrence of fragility fractures in the third trimester or early postpartum. OBJECTIVE: To investigate the changes in bone mineral density (BMD) and bone turnover markers in patients with PLO with and without TPTD treatment. DESIGN: Retrospective cohort study. PATIENTS: Thirty-two patients with PLO who presented w

Serum PTHrP levels predicted cancer-associated WL independent of the presence of hypercalcemia, inflammation, tumor burden, and other comorbidities.

Dual-energy X-ray absorptiometry (DXA)-based bone mineral density testing is standard to diagnose osteoporosis to detect individuals at high risk of fracture. A radiomics approach to extract quantifiable texture features from DXA hip images may improve hip fracture prediction without additional costs. Here, we investigated whether bone radiomics scores from DXA hip images could improve hip fracture prediction in a community-based cohort of older women. The derivation set (143 women who sustained

Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and metabolism where ML principles have been actively deployed. Relevant studies are discussed to provide an overview of the methodology, main findings, and limitations of ML, with the goal of stimulating insights into future research directions. Clear, testable study hypotheses stem fro

Ezetimibe-statin combination therapy was associated with greater cardiovascular benefits in patients with diabetes than in those without diabetes. Our findings suggest that ezetimibe-statin combination therapy might be a useful strategy in patients with diabetes at a residual risk of MACEs.

BACKGROUND: Early detection and management of sarcopenia is of clinical importance. We aimed to develop a chest X-ray-based deep learning model to predict presence of sarcopenia. METHODS: Data of participants who visited osteoporosis clinic at Severance Hospital, Seoul, South Korea, between January 2020 and June 2021 were used as derivation cohort as split to train, validation and test set (65:15:20). A community-based older adults cohort (KURE) was used as external test set. Sarcopenia was defi

PURPOSE: The Korean Urban Rural Elderly (KURE) cohort was initiated to study the epidemiologic characteristics, physical performance, laboratory and imaging biomarkers and incidence of age-related diseases in an elderly population with respect to both clinical and social aspects to develop preventive and therapeutic strategies for combatting age-related diseases. PARTICIPANTS: A total of 3517 adults aged 65 or older participated in the cohort at baseline from 2012 to 2015, recruited from three u

CONTEXT: Data on longitudinal changes of computed tomography (CT)-determined visceral fat area (VFA), skeletal muscle area (SMA) and skeletal muscle radiodensity (SMD) after adrenalectomy are limited in patients with hypercortisolism. OBJECTIVE: To examine the association of severity of cortisol excess and improvement of CT-based muscle and fat parameters after adrenalectomy. DESIGN: Retrospective observational cohort study. PATIENTS: One hundred thirty-four patients with overt Cushing's syndrom