OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

OBJECTIVES: This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices’ predictive ability with that of the body mass index (BMI). METHODS: We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index). RESULTS: Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant. CONCLUSIONS In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Background: Turner syndrome (TS) is a common chromosomal abnormality, which is caused by loss of all or part of one X chromosome. Hormone replacement therapy in TS is important in terms of puberty, growth and prevention of osteoporosis however, such a study has never been conducted in Korea. Therefore, the purpose of our study was to determine relationship between the starting age, duration of estrogen replacement therapy (ERT) in TS and develop a hormone replacement protocol suitable for the situation in Korea. Methods: This is retrospective study analyzed the medical records in TS patients treated at the Severance hospital, Yonsei University College of Medicine, Seoul, Korea from 1997 to 2019. Total of 188 subjects who had received a bone density test at least once were included in the study. Korean National Health and Nutrition Examination Survey (KNHANES) was used for achieving bone mineral density (BMD) of normal control group. Student’s t-test, MannWhitney U test, ANOVA and correlation analysis were performed using SPSS 18.0. Results: Each BMD measurement was significantly lower in women with TS than in healthy Korean women. Early start and longer duration of ERT is associated with higher lumbar spine BMD but not femur neck BMD. Femur neck BMD, but not lumbar spine BMD was significantly higher in women with mosaicism than 45XO group. Conclusion Early onset and appropriate duration of hormone replacement therapy is important for increasing bone mineral density in patients with Turner syndrome. Also, ERT affects differently to TS patients according to mosaicism.

Osteoarthritis (OA) is the most common arthritis globally. Besides cartilage loss, all surrounding structures of the joint, including the synovium, capsule, ligament, bone, nerve, and muscle, are affected by this disease, resulting in joint failure. The traditional diagnosis of OA depends on clinical symptoms, physical examination, and radiographic findings. Ultrasonography (US), computed tomography, and magnetic resonance imaging (MRI) are imaging modalities commonly used for assessing OA.Current Concepts: US findings of OA indicate synovitis, hyaline and fibrous cartilage damage, ligament and tendon changes, and bony abnormalities. US is clinically useful because it correlates with the clinical pain index and radiographic and MRI findings, differentiates the various causes of OA pain, helps diagnose early disease, predicts prognosis, and increases the accuracy and safety of intra-articular injections in OA joints.Discussion and Conclusion: Although US has some limitations as a tool for examining whole joint structures, its use is predicted to increase in the future because it is beneficial and easily accessible for assessing OA. To produce accurate US results, the examiner should have deep anatomical knowledge and skilled practice techniques, and a clinical diagnosis should be performed based on clinical symptoms and physical examination.

Background: Hand hygiene is considered the simplest and most cost-effective method of infection prevention. Regular observation and feedback on hand hygiene compliance are key strategies for its enhancement. This study evaluated the effectiveness of hand hygiene surveillance, including direct observation and feedback, by comprehensively analyzing the reported hand hygiene compliance within the Korean National Healthcare-Associated Infections Surveillance System from 2019 to 2022. Methods: Participating medical institutions included general hospitals and hospitals with infection control departments that consented to participate. Hand hygiene surveillance was conducted using direct observation. Collected data, including healthcare workers, clinical areas, hand hygiene moments, and hand hygiene compliance, were recorded to calculate hand hygiene compliance rates. Additionally, the volume of alcohol-based hand sanitizers used per patient per day was investigated as an indirect indicator of hand hygiene compliance. The study was conducted from July 2019 to December 2022. Results: Hand hygiene compliance increased from 87.2% in Q3 2019 to 89.9% in 2022. Nurses and medical technologists showed the highest compliance rates, whereas doctors showed the lowest compliance rates. Intensive care units excelled in compliance, whereas emergency de partments lagged. Compliance was highest after patient contact and lowest when the patient’s surroundings were touched. Larger hospitals consumed more alcohol-based hand sanitizers than smaller hospitals did. Conclusion This study confirmed an improvement in hand hygiene compliance through sustained surveillance, indicating its contribution not only to preventing infection transfer within healthcare facilities but also to fostering a culture of hand hygiene in the country.

OBJECTIVES: This study investigated whether Janus kinase inhibitors (JAKis) raise the risk of cardiovascular disease (CVD), venous thromboembolism (VTE), and cancer in patients with rheumatoid arthritis (RA). METHODS: We conducted a real-world retrospective observational study using data obtained from the Korean National Health Insurance Service database. Two data sets were analyzed: tumor necrosis factor inhibitor (TNFi)/JAKi-naive RA patients (set 1) and all RA patients who used TNFis or JAKis (set 2). The incidence rate ratios (IRRs) and hazard ratios (HRs) for acute myocardial infarction (AMI), stroke, cardiovascular (CV)-related mortality, major adverse cardiovascular events (MACE), VTE, arterial thromboembolism (ATE), cancer, and all-cause mortality were compared between the JAKi and TNFi groups. RESULTS: Set 1 included 1,596 RA patients (JAKi group: 645; TNFi group: 951), and set 2 included 11,765 RA patients (JAKi group: 2,498; TNFi group: 9,267). No adverse events (AEs) showed significantly higher IRRs in the JAKi groups than in the TNFi groups of sets 1 and 2. The HRs for MACE in the JAKi groups of sets 1 and 2 were 0.59 (95% confidence [CI], 0.35 to 0.99) and 0.80 (95% CI, 0.67 to 0.97), respectively. The JAKi group of set 2 showed a significantly higher risk of all-cause mortality (HR, 1.71; 95% CI, 1.32 to 2.20), but the other AEs did not demonstrate increased risks in the JAKi groups. CONCLUSIONS In this study, JAKis did not increase the risk of AMI, stroke, CV-related mortality, MACE, VTE, ATE, or cancer in Korean RA patients relative to TNFis.

Objectives: This study used the Korean National Health and Nutrition Examination Survey (KNHANES) to determine the association between fractures and low muscle mass. Methods: This cross-sectional study used the 2010–2011 KNHANES data. Low muscle mass was defined as (appendicular skeletal muscle mass [kg]/Height2 [m2 ]) < 5.45 kg/m2 , which is < 2 SD below the sex-specific mean of a young reference group. Patients with T-scores between –1.0 and –2.5 indicated osteopenia, whereas those with T-scores lower than –2.5 indicated osteoporosis. Results: Out of 1,306 women enrolled in the study, 330 were diagnosed with low muscle mass according to the abovementioned diagnostic criterion. The prevalence of fractures at various sites was significantly higher in postmenopausal women with low muscle mass than in those without low muscle mass (relative risk [RR], 1.64; odds ratio [OR], 1.62; 95% confidence interval [CI], 1.06–2.48; P = 0.027). Furthermore, the prevalence of fractures was increased by the presence of osteopenia or osteoporosis in addition to low muscle mass (RR, 1.59; OR, 1.60; 95% CI, 1.02–2.49; P = 0.039) and by osteoporosis only (RR, 2.12; OR, 2.29; 95% CI, 1.11–4.70; P = 0.025). Conclusions Fracture was more prevalent in postmenopausal women with low muscle mass than in those without low muscle mass.This finding is consistent in a subgroup analysis that included women who had osteoporosis or osteopenia. Moreover, the risk of fractures increased as low muscle mass worsened.