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.

Background/Aims: Krebs von den Lungen-6 (KL-6) is associated with prognosis in patients with COVID-19. However, there is limited data on the correlation between the prognosis of COVID-19 and varying KL-6 levels at different time points. We investigated the optimal cutoff values of the initial and peak serum KL-6 levels to predict mortality and evaluated their correlation with mortality. Methods: This retrospective cohort study collected data on serially collected serum KL-6 levels in patients hospitalized with COVID-19 between October 2020 and January 2022 at a single tertiary hospital in South Korea. The area under the receiver operating characteristic curve and Youden index were used to determine the cutoff points for the initial and peak KL-6 levels that best predicted 30-day mortality. The association between the initial and peak KL-6 values was assessed by univariate and multivariate logistic regression models. Results: A total of 349 patients were included in this study. The mean initial and peak KL-6 levels were significantly higher in the non-survivor group than in the survivor group. The initial and peak KL-6 values that best predicted 30-day mortality were 491.85 U/mL and 660.05 U/mL, respectively. An initial KL-6 level greater than 491.85 U/mL and a peak KL-6 level greater than 660.05 U/mL were significantly associated with 30-day mortality. Conclusions The initial and peak levels of KL-6 were significantly associated with 30-day mortality in hospitalized patients with COVID-19. These findings suggest that serially monitoring blood KL-6 levels could be a valuable prognostic indicator for COVID-19.

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.

Background/Aims: Krebs von den Lungen-6 (KL-6) is associated with prognosis in patients with COVID-19. However, there is limited data on the correlation between the prognosis of COVID-19 and varying KL-6 levels at different time points. We investigated the optimal cutoff values of the initial and peak serum KL-6 levels to predict mortality and evaluated their correlation with mortality. Methods: This retrospective cohort study collected data on serially collected serum KL-6 levels in patients hospitalized with COVID-19 between October 2020 and January 2022 at a single tertiary hospital in South Korea. The area under the receiver operating characteristic curve and Youden index were used to determine the cutoff points for the initial and peak KL-6 levels that best predicted 30-day mortality. The association between the initial and peak KL-6 values was assessed by univariate and multivariate logistic regression models. Results: A total of 349 patients were included in this study. The mean initial and peak KL-6 levels were significantly higher in the non-survivor group than in the survivor group. The initial and peak KL-6 values that best predicted 30-day mortality were 491.85 U/mL and 660.05 U/mL, respectively. An initial KL-6 level greater than 491.85 U/mL and a peak KL-6 level greater than 660.05 U/mL were significantly associated with 30-day mortality. Conclusions The initial and peak levels of KL-6 were significantly associated with 30-day mortality in hospitalized patients with COVID-19. These findings suggest that serially monitoring blood KL-6 levels could be a valuable prognostic indicator for COVID-19.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.