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 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 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 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: This study investigated the real-world efficacy and safety of insulin degludec/insulin aspart (IDegAsp) in Korean adults with type 2 diabetes mellitus (T2DM), whose insulin treatment was switched to IDegAsp. Methods: This was a multicenter, retrospective, observational study comprising two 26-week treatment periods, before and after switching to IDegAsp, respectively. Korean adults with uncontrolled T2DM treated with basal or premix insulin (±oral antidiabetic drugs) were enrolled. The primary objective was to compare the degree of glycosylated hemoglobin (HbA1c) change in each 26-week observation period. The analyses included changes in HbA1c, fasting plasma glucose (FPG), body weight, proportion of participants achieving HbA1c <7.0%, hypoglycemic events, and total daily insulin dose (ClinicalTrials.gov, number NCT04656106). Results: In total, 196 adults (mean age, 65.95 years; mean T2DM duration, 18.99 years) were analyzed. The change in both HbA1c and FPG were significantly different between the pre-switching and the post-switching period (0.28% vs. –0.51%, P<0.001; 5.21 mg/dL vs. –23.10 mg/dL, P=0.005), respectively. After switching, the rate of achieving HbA1c <7.0% was significantly improved (5.10% at baseline vs. 11.22% with IDegAsp, P=0.012). No significant differences (before vs. after switching) were observed in body weight change, and total daily insulin dose. The rates of overall and severe hypoglycemia were similar in the two periods. Conclusion In real-world clinical practice in Korea, the change of insulin regimen to IDegAsp was associated with an improvement in glycemic control without increase of hypoglycemia, supporting the use of IDegAsp for patients with T2DM uncontrolled with basal or premix insulin.

Background: This study examined the distribution of stress-cortisol responses and risk factors affecting perceived stress and cortisol responses among 187 university students in South Korea. Methods: Perceived stress, depressive symptoms, and health-promoting lifestyle were assessed using structured questionnaires. Blood analyses and anthropometrics were used to determine cortisol and cardiometabolic risks. Multinomial logistic regression analysis was used to examine the factors affecting stress-cortisol responses. Results: Four groups of stress-cortisol responses were found, including normal (39.0%), high stress (34.8%), high stress-cortisol (13.9%), and high cortisol group (12.3%). Age, systolic blood pressure, high-density lipoprotein cholesterol, depressive symptoms, and physical activity were associated with stress-cortisol responses. Conclusions Multidimensional interventions are needed to reduce stress levels and promote normal stress-cortisol responses.

Diabetes care has experienced great changes due to technological advancements. Recent notable innovations in diabetes technology include real-time continuous glucose monitors, automated insulin delivery systems, insulin patches, and health management applications based on smartwatches and smartphones. Along with the development of these digital devices, there have been efforts to integrate patient-generated health data, including blood glucose/blood pressure, diet, exercise, and sleep, with hospital electronic health records for direct use in diabetes care. In addition, advancements and cost reductions in omics technologies, including genomics, are expected to enable personalized diagnosis, treatment, and prevention of diabetes through modeling based on vast amounts of related data, from multi-omics to patient-generated health data, using artificial intelligence. This is ultimately expected to advance precision medicine for diabetes in the future.

Objective: We aimed to assess the level of public awareness regarding dyslipidemia and its management among the Korean population. Methods: We conducted a web- or mobile-based survey study targeting the general population, using various recruitment methods, between July 25, 2022 and August 26, 2022.The questionnaire consisted of 12 questions designed to collect demographic information and evaluate participants’ awareness and knowledge about dyslipidemia. Results: In total, 2,882 participants who completed the survey were included in the analysis.Among the participants, a substantial majority (89.1%) were familiar with the concepts of “good cholesterol” and “bad cholesterol,” while a comparatively lower percentage (just 46.7%) were acquainted with the term “dyslipidemia.” Noticeable variations in understanding were observed when examining specific aspects of dyslipidemia management, including diet, exercise, and pharmacotherapy. Conclusion The results of this survey underscore the significance of enhancing public awareness about dyslipidemia within the context of health literacy, demonstrating the necessity for a more comprehensive approach that includes education and policymaking to effectively manage dyslipidemia.

Objective: This study aimed to investigate the prevalence and status of dyslipidemia management among South Korean adults, as performed by the Korean Society of Lipid and Atherosclerosis under the name Dyslipidemia Fact Sheet 2022. Methods: We analyzed the lipid profiles, age-standardized and crude prevalence, management status of hypercholesterolemia and dyslipidemia, and health behaviors among Korean adults aged ≥20 years, using the Korea National Health and Nutrition Examination Survey data between 2007 and 2020. Results: In South Korea, the crude prevalence of hypercholesterolemia (total cholesterol ≥240 mg/dL or use of a lipid-lowering drug) in 2020 was 24%, and the age-standardized prevalence of hypercholesterolemia more than doubled from 2007 to 2020. The crude treatment rate was 55.2%, and the control rate was 47.7%. The crude prevalence of dyslipidemia (more than one out of three conditions [low-density lipoprotein-cholesterol ≥160 or the use of a lipid-lowering drug, triglycerides ≥200, or high-density lipoprotein-cholesterol (men and women) <40 mg/ dL]) was 40.2% between 2016 and 2020. However, it increased to 48.2% when the definition of hypo-high-density lipoprotein-cholesterolemia in women changed from <40 to <50 mg/dL. Conclusion Although the prevalence of hypercholesterolemia and dyslipidemia has steadily increased in South Korea, the treatment rate remains low. Therefore, continuous efforts are needed to manage dyslipidemia through cooperation between the national healthcare system, patients, and healthcare providers.