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: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

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.

To ensure high-quality bioresources and standardize biobanks, there is an urgent need to develop and disseminate educational training programs in accordance with ISO 20387, which was developed in 2018. The standardization of biobank education programs is also required to train biobank experts. The subdivision of categories and levels of education is necessary for jobs such as operations manager (bank president), quality manager, practitioner, and administrator. Essential training includes programs tailored for beginner, intermediate, and advanced practitioners, along with customized training for operations managers. We reviewed and studied ways to develop an appropriate range of education and training opportunities for standard biobanking education and the training of experts based on KS J ISO 20387. We propose more systematic and professional biobanking training programs in accordance with ISO 20387, in addition to the certification programs of the National Biobank and the Korean Laboratory Accreditation System. We suggest various training programs appropriate to a student’s affiliation or work, such as university biobanking specialized education, short-term job training at unit biobanks, biobank research institute symposiums by the Korean Society of Pathologists, and education programs for biobankers and researchers. Through these various education programs, we expect that Korean biobanks will satisfy global standards, meet the needs of users and researchers, and contribute to the advancement of science.

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.

Purpose: The purpose of this study was to develop an approach to alleviate the discomfort caused by sandbag compression after a bone marrow examination. This research examined the effects of applying a pressure hemostasis band on bleeding, pain, and discomfort at the bone marrow examination site. Methods: This study was conducted with a nonequivalent control group non-synchronized design. For 74 patients under evaluation who underwent bone marrow examination, sandbag compression was applied to the examination site in the control group (n=37), and a pressure hemostasis band was applied to the intervention group (n=37). In both groups, absolute bed rest was performed for two hours, and bleeding, pain, and discomfort at the examination site were measured. Results: After two hours of the bone marrow examination, there was no difference in bleeding on the gauze between the two groups (F=0.59, p=.444). Bleeding occurred in three patients in the intervention group and six in the control group (χ 2 =1.14, p=.479), with no cases of hematoma detected in either group. One hour post-examination, the control group experienced significantly higher pain (F=5.45, p=.022) and discomfort (F=5.68, p=.020) than the intervention group. However, pain and discomfort levels were similar between groups after two hours. Conclusion Compared to the sandbag compression group, the band application group showed no difference in bleeding and experienced less pain and discomfort at the examination site. This confirms that the pressure hemostasis band is a suitable alternative to sandbag compression in post-examination care.

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: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

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: 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.