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 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.

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.

Background: Commutability refers to the consistency of results from different measurement procedures in regards to a reference material (RM) and representative samples. In this study, we evaluated the commutability of laboratory-prepared pooled sera and commercial quality control materials in the thyroid-stimulating hormone (TSH) proficiency testing program of the Korean Association of External Quality Assessment Service. Methods: Serum TSH from 30 patients was measured in triplicate. Two levels of lab-prepared pooled sera and three levels of commercial materials (Bio-Rad Liquichek Immunoassay Plus) were tested in triplicate at five positions per immunoassay platform (Beckman Coulter UniCel DxI 800, Abbott Alinity i, Roche Cobas e801, Siemens Atellica IM 1600). Commutability was assessed by comparing method differences in patient samples to RMs using the ‘International Federation of Clinical Chemistry and Laboratory Medicine’ protocol with a desirable bias of 10% based on biological variation. Results: The median TSH level for the 30 patient samples was 2.51–3.07 μIU/mL, with a coefficient of variation ranging from 1.51% to 4.32%.The median TSH levels of the in-house prepared materials were 0.912– 1.01 μIU/mL for RM2 and 9.10–10.9 μIU/mL for RM4. The median TSH levels of the commercial materials were 0.391–0.464 μIU/mL for RM1, 4.39–5.24 μIU/mL for RM3, and 28.2–35.5 μIU/mL for RM5. The in-house prepared materials (RM2, RM4) demonstrated commutability across all six method combinations. Among the commercial materials, RM1 and RM3 showed commutability in four method combinations, while RM5 showed commutability in three method combinations. Conclusions The evaluation results for the TSH proficiency testing materials showed that the in-house prepared materials had higher commutability than the commercial materials.