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: Humans are exposed to mercury primarily in its highly toxic form, methyl mercury, which is known to have adverse effects on various organs and systems. The negative impact of mercury exposure on the growth, development, and mental health of children, from infancy to adolescence, is well-documented. However, there are no internationally standardized safe limits for mercury exposure. This study investigated the impact of dietary habits and higher body mass index (BMI) on blood mercury levels in adolescents. Methods: This study analyzed the data from the 4th Korean National Environmental Health Survey (KoNEHS) 2018–2020. The focus was on 825 middle and high school students aged 13–18 years, whose blood mercury levels were measured. A survey on dietary and lifestyle habits was also conducted. Blood mercury levels were categorized by geometric median values, and associations with overweight status and seafood consumption were examined using a generalized linear model. Results: The geometric mean blood mercury level for the entire sample was 1.37 μg/L, with levels of 1.31 μg/L in normal-weight individuals and 1.43 μg/L in overweight individuals, showing a statistically significant difference between the two groups. After adjusting for other variables, blood mercury levels were significantly associated with overweight status (estimate: 0.084; p = 0.018; 95% confidence interval [CI]: 0.015–0.153), consumption of large fish and tuna more than once a week (estimate: 0.18; p = 0.001; 95% CI: 0.077–0.284), and consumption of fish once a week or more (estimate: 0.147; p = 0.004; 95% CI: 0.043–0.250). Conclusions In adolescents, a higher BMI and an increased consumption of large fish, tuna, and fish were associated with higher blood mercury levels. Notably, a stronger association was found between large fish consumption and blood mercury levels in the overweight group. These findings suggest the need to moderate seafood consumption and establish more proactive mercury exposure standards for adolescents.

Background and Objectives: Kawasaki disease (KD) is an acute vasculitis that primarily affects children under age 5 years. Approximately 20–25% of untreated children with KD and 3–5% of those treated with intravenous immunoglobulin therapy develop coronary artery aneurysms (CAAs). The prevalence of CAAs is much higher in male than in female patients with KD, but the underlying factors contributing to susceptibility to CAAs in patients with KD remain unclear. This study aimed to identify sex-specific susceptibility loci associated with CAAs in KD patients. Methods: A sex-stratified genome-wide association study (GWAS) was performed using previously obtained GWAS data from 296 KD patients and a new replication study in an independent set of 976 KD patients by comparing KD patients without CAA (controls) and KD patients with aneurysms (internal diameter ≥5 mm) (cases). Results: Six male-specific susceptibility loci, PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ (odds ratios [ORs], 2.25–9.98; p=0.00204–1.96×10−6 ), and 2 female-specific susceptibility loci, SMAD3 (OR, 4.59; p=0.00016) and IL1RAPL1 (OR, 4.35; p=0.00026), were significantly associated with CAAs in patients with KD. In addition, the numbers of CAA risk alleles additively contributed to the development of CAAs in patients with KD. Conclusions A sex-stratified GWAS identified 6 male-specific (PDE1C, NOS3, DLG2, CPNE8, FUNDC1, and GABRQ) and 2 female-specific (SMAD3 and IL1RAPL1) CAA susceptibility loci in patients with KD.