Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Background/Aims: Findings on the impact of Helicobacter pylori eradication on metabolic parameters are inconsistent. This study aimed to evaluate the effects of H. pylori eradication on metabolic parameters and body composition, including body fat mass and skeletal muscle mass. Methods: We retrospectively reviewed the data of asymptomatic patients who underwent health screenings, including bioelectrical impedance analysis, before and after H. pylori eradication between 2005 and 2021. After matching individuals based on key factors, we compared lipid profiles, metabolic parameters, and body composition between 823 patients from the eradicated group and 823 patients from the non-eradicated groups. Results: Blood pressure, erythrocyte sedimentation rate, and glycated hemoglobin values were significantly lower in the eradicated group than in the non-eradicated group. However, changes in body mass index (BMI), body fat mass, appendicular skeletal muscle mass (ASM), waist circumference, and lipid profiles were not significantly different between the two groups. In a subgroup analysis of individuals aged >45 years, blood pressure, erythrocyte sedimentation rate, and glycated hemoglobin changes were significantly lower in the eradicated group than in the noneradicated group. BMI values were significantly higher in the eradicated group than in the noneradicated group; however, no significant differences were observed between the two groups regarding changes in body weight, body fat mass, ASM, or waist circumference. Total cholesterol and low-density lipoprotein cholesterol levels were significantly lower in the eradicated group than in non-eradicated group. Conclusions H. pylori eradication significantly reduced blood pressure, glucose levels, and systemic inflammation and improved lipid profiles in patients aged >45 years. BMI, body fat mass, ASM, and waist circumference did not significantly differ between patients in the eradicated group and those in the non-eradicated group.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Objective: Stigma influences perceptions of mental illness and novel diseases like coronavirus disease-2019 (COVID-19), often impeding healthcare access despite advancements in medical treatment. This study compares the stigma associated with COVID-19 and mental illness to identify factors that could help reduce stigma. Methods: An online survey was conducted in May 2023 among 1,500 participants aged 19 to 65 in South Korea, using a panel from Embrain, an online survey service. The survey assessed stigma and distress related to COVID-19 and mental illness using a validated questionnaire. It collected demographic and clinical data, evaluated COVID-19-related stigma, fear, and knowledge, and measured prejudice and attitudes toward psychiatric treatment. Personality traits were assessed using the Big Five Inventory (BFI)-10. Factors significantly associated with stigma scores were entered into linear regression analysis. Results: COVID-19-related stigma scores were significantly negatively correlated with knowledge of COVID-19 and positively correlated with fear of infection and age. Individuals with a history of COVID-19 infection had significantly lower scores on COVID-19-related stigma. Similarly, mental illness stigma was negatively correlated with knowledge of psychiatric treatment and positively correlated with age, as well as conscientiousness and neuroticism in the BFI. Personal experience with individuals with mental illness was associated with significantly lower stigma scores. Conclusion This study suggests that the mechanism-making stigma was similar in cases of traditional mental illness and a novel infectious disease. Both cognitive and experiential factors influence stigma. Educating the public about the disease and enabling interactions with affected individuals emerge as effective strategies for stigma reduction.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.