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: With the introduction of disease-modifying treatments for Alzheimer’s disease (AD), less invasive and widely accessible screening tests are urgently needed. We assessed eight blood-based biomarkers in a well-defined cohort of preclinical AD, including participants with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Methods: Amyloid beta (Aβ) oligomerization tendency, Aβ42, Aβ40, Aβ42/Aβ40 ratio, phosphorylated tau (p-tau)181, p-tau217, glial fibrillary acidic protein (GFAP), and neurofilament light (Nf-L) were assessed for distinguishing between SCD and MCI, for correlations, and for predicting Aβ positron emission tomography (PET) positivity. Results: Plasma p-tau181, p-tau217, and GFAP levels were significantly higher in participants with MCI than in those with SCD (P < 0.05) and in Aβ PET-positive versus Aβ PET-negative participants (P < 0.0001), whereas plasma Aβ42 and Aβ42/40 ratio levels were significantly lower in Aβ PET-positive than in Aβ PET-negative participants (P < 0.001). Logistic regression analysis revealed that plasma Aβ42 and p-tau217 levels predicted Aβ PET positivity with an area under the ROC curve (AUC) of 0.930 (95% confidence interval [CI], 0.848–0.976) in the entire cohort, and p-tau217 alone predicted Aβ PET-positivity with an AUC of 0.887 (95% CI, 0.779–0.954) in the MCI subgroup. Conclusions Plasma p-tau217 levels outperform plasma p-tau181 levels in predicting Aβ PET-positivity in participants with preclinical AD. Plasma GFAP levels, along with different ptau isoforms (p-tau181 and p-tau217), effectively differentiate MCI from SCD. The predictive accuracy of blood-based biomarkers for Aβ PET-positivity strongly supports their clinical implementation, particularly with the introduction of disease-modifying therapies.

Background: The direct method for reference interval (RI) estimating is limited due to the requirement of resources, difficulties in defining a non-diseased population, or ethical problems in obtaining samples. We estimated the RI for inflammatory biomarkers using an indirect method (RII). Methods: C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and presepsin (PSEP) data of patients visiting a single hospital were retrieved from April 2009 to April 2021. Right-skewed data were transformed using the Box-Cox transformation method. A mixed population of non-diseased and diseased distributions was assumed, followed by latent profile analysis for the two classes. The intersection point of the distribution curve was estimated as the RI. The influence of measurement size was evaluated as the ratio of abnormal values and adjustment (n×bandwidth) of the distribution curve. Results: The RIs estimated by the proposed RII method (existing method) were as follows: CRP, 0–4.1 (0–4.7) mg/L; ESR, 0–10.2 (0–15) mm/hr and PSEP, 0–411 (0–300) pg/mL. Measurement sizes ≥2,500 showed stable results. An abnormal-to-normal value ratio of 0.5 showed the most accurate result for CRP. Adjustment values ≤5 or >5 were applicable for a measurement size <25,000 or ≥25,000, respectively. Conclusions The proposed RII method could provide additional information for RI verification or estimation with some limitations.

Background: We evaluated the diagnostic performance of the Exdia COVID-19 antigen test (Exdia Ag; Precision Biosensor Inc., Korea) as a point-of-care (POC) test performed in the emergency department (ED) for the rapid detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in comparison with the performance of the Real-Q 2019-nCoV Detection KIT (Real-Q; BioSewoom, Korea). Methods: Exdia Ag and Real-Q assays were performed simultaneously for all patients who were admitted to the ED with or without COVID-19 symptoms between December 2021 and March 2022. Results: Among the 2,523 samples analyzed by Real-Q assay, 149 samples (5.9%) showed positive results, and 2,374 samples showed negative results. The overall sensitivity and specificity of the Exdia Ag assay were 77.2% (95% confidence interval [CI], 69.6 – 83.7) and 99.8% (95% CI, 99.6 – 99.9), respectively. The positive and negative predictive values were 96.6% (95% CI, 91.5 – 98.7) and 98.6% (95% CI, 98.1 – 98.9), respectively. The cycle threshold value for 115 concordant Exdia Ag-positive/Real-Q-positive samples was significantly lower than that for 34 discordant Exdia Ag-negative/Real-Q-positive samples (P < 0.0001) Conclusion The Exdia Ag assay showed good diagnostic performance when the disease prevalence was high and may be useful for POC testing when the rapid detection of SARSCoV-2 is required for the isolation of patients in the ED.

Objectives: . Inferior turbinate (IT) hypertrophy is the main cause of chronic nasal obstruction. We developed a high-intensity focused ultrasound (HIFU) ablation device to treat patients with IT hypertrophy. Methods: . First, computed tomography images of patients with no evidence of sinonasal disease were evaluated to measure and compare the IT, medial mucosal thickness (MT), and space between the nasal septum and IT according to clinical characteristics such as septal deviation. A HIFU prototype was developed based on the above human anatomical studies. The experimental study was performed in five pigs; the nasal volume and histological changes at 1 and 4 weeks postoperatively were evaluated to compare the efficacy of HIFU turbinoplasty with that of radiofrequency turbinoplasty and a control group. Results: . The mean medial MT of the anterior, middle, and posterior portions of the IT were 4.66±1.14, 4.23±0.97, and 6.17±1.29 mm, respectively. The mean medial space was 2.65±0.79 mm. The diameter and focal depth of the prototype were 4 mm and 3 mm, respectively. HIFU showed no postoperative complications, including bleeding or scar formation. After HIFU treatment, the nasal volume increased by 196.62 mm3 (7.8%) and 193.74 mm3 (8.3%) at 1 week and 4 weeks, compared with the increase of 87.20 mm3 (3.1%) and 213.81 mm3 (9.0%), respectively,after radiofrequency therapy. A qualitative histological analysis after radiofrequency turbinoplasty showed epithelial layer disruption at 1 week and increased fibrosis, along with decreased glandular structure, at 4 weeks. The HIFU group had an intact epithelial layer at 1 week postoperatively. However, significant differences were observed at 4 weeks, including increased fibrosis and decreased glandular structure. Conclusion . The efficacy and safety of HIFU turbinoplasty were demonstrated in an animal study. Our results warrant further human clinical trials.

Background: Hepatocellular carcinoma (HCC) is the second-most-common cause of cancer-related deaths worldwide, and an accurate and non-invasive biomarker for the early detection and monitoring of HCC is required. We assessed pathogenic variants of HCC driver genes in cell-free DNA (cfDNA) from HCC patients who had not undergone systemic therapy. Methods: Plasma cfDNA was collected from 20 HCC patients, and deep sequencing was performed using a customized cfDNA next-generation sequencing panel, targeting the major HCC driver genes (TP53, CTNNB1, TERT) that incorporates molecular barcoding. Results: In 13/20 (65%) patients, we identified at least one pathogenic variant of two major HCC driver genes (TP53 and CTNNB1), including 16 variants of TP53 and nine variants of CTNNB1. The TP53 and CTNNB1 variants showed low allele frequencies, with median values of 0.17% (range: 0.06%–6.99%) and 0.07% (range: 0.05%–0.96%), respectively. However, the molecular coverage of variants was sufficient, with median values of 5,543 (range: 2,317–9,088) and 7,568 (range: 2,400–9,633) for TP53 and CTNNB1 variants, respectively. Conclusions Our targeted DNA sequencing successfully identified low-frequency pathogenic variants in the cfDNA from HCC patients by achieving high coverage of unique molecular families. Our results support the utility of cfDNA analysis to identify somatic gene variants in HCC patients.