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.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Granular cell tumor is a rare disease, and it is even rarer in the male breast. Although it is typically a benign tumor, due to its features and image findings, it can be easily misdiagnosed and managed as a malignant tumor. Therefore, the extent of the surgery can inappropriately be expanded. To avoid misdiagnosis and overtreatment, surgeons must perform a careful evaluation. We describe a case of a granular cell tumor of the male breast treated with mastectomy.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Background/Aims: Metabolic dysfunction-associated fatty liver disease (MAFLD) is categorized into three subtypes: overweight/obese (OW), leanormal weight with metabolic abnormalities, and diabetes mellitus (DM). We investigated whether fibrotic burden in liver differs across subtypes of MAFLD patients. Methods: This cross-sectional multicenter study was done in cohorts of subjects who underwent a comprehensive medical health checkup between January 2014 and December 2020. A total of 42,651 patients with ultrasound-diagnosed fatty liver were included. Patients were classified as no MAFLD, OW-MAFLD, lean-MAFLD, and DM-MAFLD. Advanced liver fibrosis was defined based on the nonalcoholic fatty liver disease fibrosis score (NFS) or fibrosis-4 (FIB-4) index. Results: The mean age of the patients was 50.0 years, and 74.1% were male. The proportion of patients with NFS-defined advanced liver fibrosis was the highest in DM-MAFLD (6.6%), followed by OW-MAFLD (2.0%), lean-MAFLD (1.3%), and no MAFLD (0.2%). The proportion of patients with FIB-4-defined advanced liver fibrosis was the highest in DM-MAFLD (8.6%), followed by lean-MAFLD (3.9%), OW-MAFLD (3.0%), and no MAFLD (2.0%). With the no MAFLD group as reference, the adjusted odds ratios (95% confidence intervals) for NFS-defined advanced liver fibrosis were 4.46 (2.09 to 9.51), 2.81 (1.12 to 6.39), and 9.52 (4.46 to 20.36) in OW-MAFLD, leanMAFLD, and DM-MAFLD, respectively, and the adjusted odds ratios for FIB-4-defined advanced liver fibrosis were 1.03 (0.78 to 1.36), 1.14 (0.82 to 1.57), and 1.97 (1.48 to 2.62) in OW-MAFLD, lean-MAFLD, and DM-MAFLD. Conclusions Fibrotic burden in the liver differs across MAFLD subtypes. Optimized surveillance strategies and therapeutic options might be needed for different MAFLD subtypes.

Objective: To investigate the relationship between reduced glutathione (GSH), a key molecule of the antioxidant defense system in the blood, and glutathione reductase (GR), which reduces oxidized glutathione (glutathione disulfide [GSSG]) to GSH and maintains the redox balance, with the prevalence of Alzheimer’s dementia and cognitive decline. Methods: In all, 20 participants with Alzheimer’s dementia who completed the third follow-up clinical evaluation over 6 years were selected, and 20 participants with normal cognition were selected after age and sex matching. The GSH and GR concentrations were the independent variables. Clinical diagnosis and neurocognitive test scores were the dependent variables indicating cognitive status. Results: The higher the level of GR, the greater the possibility of having normal cognition than of developing Alzheimer’s dementia. Additionally, the higher the level of GR, the higher the neurocognitive test scores. However, this association was not significant for GSH. After 6 years, the conversion rate from normal cognition to cognitive impairment was significantly higher in the lower 50th percentile of the GR group than in the upper 50th percentile. Conclusion The higher the GR, the lower the prevalence of Alzheimer’s dementia and incidence of cognitive impairment and the higher the cognitive test scores. Therefore, GR is a potential protective biomarker against Alzheimer’s dementia and cognitive decline.

The aim of the present study was to investigate the physiological role of nicotinamide phosphoribosyltransferase (NAMPT) associated with odontogenic differentiation during tooth development in mice. Mouse dental papilla cell-23 (MDPC-23) cells cultured in differentiation media were stimulated with the specific NAMPT inhibitor, FK866, and Visfatin (NAMPT) for up to 10 days. The cells were evaluated after 0, 4, 7, and 10 days. Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. The mineralization assay was performed by staining MDPC-23 cells with Alizarin Red S solution. After cultivation, MDPC-23 cells were harvested for quantitative PCR or Western blotting. Analysis of variance was performed using StatView 5.0 software (SAS Institute Inc., Cary, NC, USA). Statistical significance was set at p < 0.05. The expression of NAMPT increased during the differentiation of murine odontoblast-like MDPC-23 cells. Furthermore, the up-regulation of NAMPT promoted odontogenic differentiation and accelerated mineralization through an increase in representative odontoblastic biomarkers, such as dentin sialophosphoprotein, dentin matrix protein-1, and alkaline phosphatase in MDPC-23 cells. However, treatment of the cells with the NAMPT inhibitor, FK866, attenuated odontogenic differentiation, as evidenced by the suppression of odontoblastic biomarkers. These data indicate that NAMPT regulated odontoblastic differentiation through the regulation of odontoblastic biomarkers. The increase in NAMPT expression in odontoblasts was closely related to the formation of the extracellular matrix and dentin via the Runx signaling pathway. Therefore, these data suggest that NAMPT is a critical regulator of odontoblast differentiation during tooth development.