Purpose: This study aimed to identify reproducible locations for evaluating masseter muscle function by measuring its thickness using ultrasonography (US). The study focused on comparing two measurement locations: the thickest part of the masseter muscle during ultrasonographic scanning (TMUS) and the most prominent part during clenching (PMC). Methods: Forty healthy adults (20 males and 20 females) participated in the study. US images were obtained from both sides of the masseter muscle under resting and clenching conditions. Measurements were taken at the TMUS and PMC locations, and the clenching-to-resting (C/R) ratio was calculated. Intra- and inter-rater reliability were assessed using intraclass correlation coefficients (ICCs), and the agreement between the two locations was further analyzed using Bland–Altman (BA) plots. Results: The measurements at both TMUS and PMC showed high intra- and inter-rater agreement, with no significant difference in measurements between the two locations.However, the PMC location demonstrated slightly higher ICC values (0.94) compared to TMUS (0.91). The C/R ratio for PMC showed higher consistency (0.89) compared to TMUS (0.65). BA plots indicated that the agreement between TMUS and PMC was slightly better during clenching than at rest, with smaller mean differences in clenching (–0.06 mm) than resting (–0.13 mm). Additionally, the number of measurements outside the upper and lower limits was lower during clenching (10) than at rest (13). Conclusions Both TMUS and PMC locations demonstrated reliable measurements, but the PMC location showed slightly better consistency across different muscle states. The findings suggest that PMC provides a more reproducible and standardized approach for masseter muscle assessment, making it a better choice for both clinical practice and research in evaluating masticatory function.

Objectives: We analyzed the demographic and clinical characteristics of patients diagnosedwith coronavirus disease 2019 (COVID-19), focusing specifically on severe/critical cases, andassessed the trends and rates of severity and fatality among these patients in the Republic of Korea. Methods: Clinical data on patients with COVID-19 from January 20, 2020 to August 30, 2023were collected from the Korea Disease Control and Prevention Agency’s database. We identified patients who progressed to severe/critical conditions and analyzed their demographic and clinical profiles. Severity and fatality rates were calculated and compared annually to track thedisease progression over time. Results: During the surveillance period, 34,572,554 COVID-19 cases were confirmed, among whom 38,112 (0.11%) progressed to severe/critical conditions. Most severe/critical cases occurred in individuals aged ≥60 years, with a notable increase in patients aged ≥80 years from 2022.The overall severity rate was 0.19%, with a fatality rate of 0.10%. However, the severity of cases gradually diminished during the study period. In 2022, the severity and fatality rates decreased to 0.14% and 0.09%, respectively. In 2023, while the severity rate remained stable at 0.15%, thefatality rate further decreased to 0.06%. Notably, throughout the study period, individuals aged ≥80 years had a significantly higher severity rate (2.44%), with a fatality rate of 1.75%. Conclusion These findings underscore the importance of prioritizing protection and management strategies for older adults and high-risk groups to mitigate the impact ofCOVID-19. Continued surveillance and analysis are essential to effectively control COVID-19 and minimize its burden on public health.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Background: The stimulatory effects of caffeine contribute to poor sleep quality. However, the relationship between caffeinated beverages and sleep quality, considering frequency or types of caffeinated beverages, were not extensively studied. Methods: Data were collected from 160 urban workers (75 men [46.9%] aged 20–69 years; with an average age of 41.8±12.3 years) using a structured, self-administered online questionnaire. Sleep quality, time, satisfaction; types and frequency of caffeinated beverages (number of cups per week; Q1: 0 cup, Q4: 14 or more cups per week), demographics, and health behaviors were asked. Sleep quality were evaluated using the Korean version of the Pittsburgh Sleep Quality Index (PSQI-K). Multiple regression analysis was conducted on the association between the frequency of caffeinated beverages consumption and sleep quality. Results: The most frequently consumed beverages were unsweetened coffee (22.8%) and the most common time for caffeine was between 12 pm to 5 pm (58.2%). The average sleep quality score based on the PSQI-K was 6.0±2.0 overall, 5.3±1.6 in Q1, and 6.6±2.2 in Q4 (frequent caffeinated beverage drinkers), indicating poorer sleep quality in Q4 (P=0.022). In Q1, 13.3% rated their sleep quality as ‘very good,’ while in Q4, only 2.5% gave the same rating. Poor sleep quality was significantly associated with the frequency of caffeinated beverages per week (β=0.232, P=0.004) and self-reported stress level (β=0.256, P=0.002). Conclusions Frequent consumption of caffeinated beverages appears to be associated with poor sleep quality among urban workers. While reducing caffeine intake may contribute to improvements in sleep quality as a health promoting behavior, this hypothesis requires validation through future studies employing personalized intervention approaches.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Objectives: We analyzed the demographic and clinical characteristics of patients diagnosedwith coronavirus disease 2019 (COVID-19), focusing specifically on severe/critical cases, andassessed the trends and rates of severity and fatality among these patients in the Republic of Korea. Methods: Clinical data on patients with COVID-19 from January 20, 2020 to August 30, 2023were collected from the Korea Disease Control and Prevention Agency’s database. We identified patients who progressed to severe/critical conditions and analyzed their demographic and clinical profiles. Severity and fatality rates were calculated and compared annually to track thedisease progression over time. Results: During the surveillance period, 34,572,554 COVID-19 cases were confirmed, among whom 38,112 (0.11%) progressed to severe/critical conditions. Most severe/critical cases occurred in individuals aged ≥60 years, with a notable increase in patients aged ≥80 years from 2022.The overall severity rate was 0.19%, with a fatality rate of 0.10%. However, the severity of cases gradually diminished during the study period. In 2022, the severity and fatality rates decreased to 0.14% and 0.09%, respectively. In 2023, while the severity rate remained stable at 0.15%, thefatality rate further decreased to 0.06%. Notably, throughout the study period, individuals aged ≥80 years had a significantly higher severity rate (2.44%), with a fatality rate of 1.75%. Conclusion These findings underscore the importance of prioritizing protection and management strategies for older adults and high-risk groups to mitigate the impact ofCOVID-19. Continued surveillance and analysis are essential to effectively control COVID-19 and minimize its burden on public health.

Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Background: The stimulatory effects of caffeine contribute to poor sleep quality. However, the relationship between caffeinated beverages and sleep quality, considering frequency or types of caffeinated beverages, were not extensively studied. Methods: Data were collected from 160 urban workers (75 men [46.9%] aged 20–69 years; with an average age of 41.8±12.3 years) using a structured, self-administered online questionnaire. Sleep quality, time, satisfaction; types and frequency of caffeinated beverages (number of cups per week; Q1: 0 cup, Q4: 14 or more cups per week), demographics, and health behaviors were asked. Sleep quality were evaluated using the Korean version of the Pittsburgh Sleep Quality Index (PSQI-K). Multiple regression analysis was conducted on the association between the frequency of caffeinated beverages consumption and sleep quality. Results: The most frequently consumed beverages were unsweetened coffee (22.8%) and the most common time for caffeine was between 12 pm to 5 pm (58.2%). The average sleep quality score based on the PSQI-K was 6.0±2.0 overall, 5.3±1.6 in Q1, and 6.6±2.2 in Q4 (frequent caffeinated beverage drinkers), indicating poorer sleep quality in Q4 (P=0.022). In Q1, 13.3% rated their sleep quality as ‘very good,’ while in Q4, only 2.5% gave the same rating. Poor sleep quality was significantly associated with the frequency of caffeinated beverages per week (β=0.232, P=0.004) and self-reported stress level (β=0.256, P=0.002). Conclusions Frequent consumption of caffeinated beverages appears to be associated with poor sleep quality among urban workers. While reducing caffeine intake may contribute to improvements in sleep quality as a health promoting behavior, this hypothesis requires validation through future studies employing personalized intervention approaches.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Objectives: We analyzed the demographic and clinical characteristics of patients diagnosedwith coronavirus disease 2019 (COVID-19), focusing specifically on severe/critical cases, andassessed the trends and rates of severity and fatality among these patients in the Republic of Korea. Methods: Clinical data on patients with COVID-19 from January 20, 2020 to August 30, 2023were collected from the Korea Disease Control and Prevention Agency’s database. We identified patients who progressed to severe/critical conditions and analyzed their demographic and clinical profiles. Severity and fatality rates were calculated and compared annually to track thedisease progression over time. Results: During the surveillance period, 34,572,554 COVID-19 cases were confirmed, among whom 38,112 (0.11%) progressed to severe/critical conditions. Most severe/critical cases occurred in individuals aged ≥60 years, with a notable increase in patients aged ≥80 years from 2022.The overall severity rate was 0.19%, with a fatality rate of 0.10%. However, the severity of cases gradually diminished during the study period. In 2022, the severity and fatality rates decreased to 0.14% and 0.09%, respectively. In 2023, while the severity rate remained stable at 0.15%, thefatality rate further decreased to 0.06%. Notably, throughout the study period, individuals aged ≥80 years had a significantly higher severity rate (2.44%), with a fatality rate of 1.75%. Conclusion These findings underscore the importance of prioritizing protection and management strategies for older adults and high-risk groups to mitigate the impact ofCOVID-19. Continued surveillance and analysis are essential to effectively control COVID-19 and minimize its burden on public health.