Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

A 6-year-old spayed female French Bulldog presented with a left-sided chest wall tumor. Physical examination revealed that the tumor was firmly adhered to the chest wall. A preoperative punch biopsy of the tumor revealed a grade 2 soft tissue sarcoma (STS). On computed tomography, the tumor’s dimensions were assessed as 6.5 × 5.7 × 3.5 cm, and it exhibited invasiveness near the tissue surrounding the ninth rib. The tumor size was large in comparison to the dog’s chest wall area. Hence, if the traditional wide-margin resection surgery were to be performed, primary wound closure seemed impractical and could potentially result in respiratory function complications. Therefore, considering the extent of tumor invasion and grade, deep margins were established to include the removal of the eighth to tenth ribs, and a 1-cm lateral margin was designated to enable primary wound closure. To reconstruct the chest wall, polypropylene mesh was attached to the adjacent ribs and the remaining muscles were sutured and covered over the mesh. The dog exhibited a rapid recovery beginning the day after the operation. Postoperative biopsy confirmed that the tumor was a grade 2 STS, and the surgical margins were evaluated as incomplete. The owner chose to pursue follow-up observation instead of chemotherapy. In this study, the surgical approach was chosen based on the importance of functional recovery after surgery. Recent research indicates that the tumor grade is more critical for postoperative prognosis than the extent of surgical margins when removing an STS.

Background: High LDL-cholesterol (LDL-C) is an established risk factor for cardiovascular disease and is considered an important therapeutic target. It can be measured directly or calculated from the results of other lipid tests. The Friedewald formula is the most widely used formula for calculating LDL-C. We modified the Friedewald formula for a more accurate and practical estimation of LDL-C. Methods: Datasets, including measured triglyceride, total cholesterol, HDL-cholesterol, and LDL-C concentrations were collected and assigned to derivation and validation sets. The datasets were further divided into five groups based on triglyceride concentrations. In the modified formula, LDL-C was defined as total cholesterol − HDL-cholesterol − (triglyceride/adjustment factor). For each group, the adjustment factor that minimized the difference between measured LDL-C and calculated LDL-C using modified formula was obtained. For validation, measured LDL-C and LDL-C calculated using the modified formula (LDL-CM), Friedewald formula (LDL-CF), Martin-Hopkins formula (LDL-CMa), and Sampson formula (LDL-CS) were compared. Results: In the derivation set, the adjustment factors were 4.7, 5.9, 6.3, and 6.4 for the groups with triglyceride concentrations <100, 101–200, 201–300, and >300 mg/dL, respectively. In the validation set, the coefficient of determination (R2) between measured and calculated LDL-C was higher for LDL-CM than for LDL-CF (R2=0.9330 vs. 0.9206). The agreement according to the National Cholesterol Education Program Adult Treatment Panel III classification of LDL-C was 86.36%, 86.08%, 86.82%, and 86.15% for LDL-CM, LDL-CF, LDL-CMa, and LDL-CS, respectively. Conclusions We proposed a practical, improved LDL-C calculation formula by applying different factors depending on the triglyceride concentration.

Background: The coronavirus disease pandemic is predicted to have adverse health effects on children and adolescents who are overweight or obese due to restricted school activity and stay-at-home orders. The purpose of this observational study was to determine the factors associated with weight gain in children and adolescents with overweight and obesity during coronavirus disease 2019 (COVID-19) lockdown. Methods: Ninety-seven participants (sex- and age-specific body mass index (BMI) ≥ 85th percentile) were included. A baseline examination was conducted pre-COVID-19 (August 2019 to January 2020), and re-examination was performed post-lockdown (June to September 2020) and the results were compared. Correlation and regression analyses were conducted to investigate the association among changes in cardiometabolic markers and lifestyle behaviors with changes in BMI z-score. Results: During the COVID-19 pandemic, an increase in BMI z-score (2.56 [2.01–2.94] to 2.62 [2.03–3.18]) was noticed in children and adolescents with obesity. Changes in cardiometabolic markers including liver enzymes, triglycerides (r = 0.398), leptin (r = 0.578), and adiponectin (r = −0.326), as well as muscular strength (r = −0.212), were correlated with the increase in BMI z-score. According to a multivariate regression analysis, changes in sedentary time (B = 0.016; 95% confidence interval [CI], 0.001–0.032) and fast-food consumption (B = 0.067; 95% CI, 0.013–0.122) were the lifestyle variables associated with BMI z-score increase. Conclusion Changes in lifestyle behaviors including fast-food consumption and sedentary time during the COVID-19 pandemic may be associated with weight gain. In order to prevent health-related risks in children and adolescents with obesity during the pandemic, it is important to maintain the level of physical activity and healthy dietary habits.

Objective: We aimed to present the study design and baseline cross-sectional participant characteristics of biobank innovations for chronic cerebrovascular disease with Alzheimer’s disease study (BICWALZS) participants. Methods: A total of 1,013 participants were enrolled in BICWALZS from October 2016 to December 2020. All participants underwent clinical assessments, basic blood tests, and standardized neuropsychological tests (n=1,013). We performed brain magnetic resonance imaging (MRI, n=817), brain amyloid positron emission tomography (PET, n=713), single nucleotide polymorphism microarray chip (K-Chip, n=949), locomotor activity assessment (actigraphy, n=200), and patient-derived dermal fibroblast sampling (n=175) on a subset of participants. Results: The mean age was 72.8 years, and 658 (65.0%) were females. Based on clinical assessments, total of 168, 534, 211, 80, and 20 had subjective cognitive decline, mild cognitive impairment (MCI), Alzheimer’s dementia, vascular dementia, and other types of dementia or not otherwise specified, respectively. Based on neuroimaging biomarkers and cognition, 199, 159, 78, and 204 were cognitively normal (CN), Alzheimer’s disease (AD)-related cognitive impairment, vascular cognitive impairment, and not otherwise specified due to mixed pathology (NOS). Each group exhibited many differences in various clinical, neuropsychological, and neuroimaging results at baseline. Baseline characteristics of BICWALZS participants in the MCI, AD, and vascular dementia groups were generally acceptable and consistent with 26 worldwide dementia cohorts and another independent AD cohort in Korea. Conclusion The BICWALZS is a prospective and longitudinal study assessing various clinical and biomarker characteristics in older adults with cognitive complaints. Details of the recruitment process, methodology, and baseline assessment results are described in this paper.

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI TM , ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.