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: The utility of the QuantiFERON-Monitor (QFM, Qiagen), a tool developed to assess general immune function, remains insufficiently explored in critically ill patients with acute respiratory failure (ARF). Therefore, we used the QFM to evaluate the immune function of patients with ARF at intensive care unit (ICU) admission and monitored QFM changes based on disease severity and clinical outcome correlations. Methods: We evaluated the immune function of 99 patients with ARF in an ICU setting.The QFM was evaluated upon ICU admission, day 7 post-ICU admission, and discharge.Their results were compared with those of five healthy controls. Results: The QFM levels at ICU admission were significantly lower in patients with ARF than in healthy controls (median IUs/mL: 5.5 vs. 465.0, respectively). The QFM levels in patients with coronavirus disease 2019 or pneumonia (9.2 and 7.9 IUs/mL, respectively) were higher than those in patients with acute respiratory distress syndrome or septic shock (4.9 and 3.6 IUs/mL, respectively). On day 7, the QFM levels increased to 8.3 IUs/ mL and reached 16.7 IUs/mL at discharge. At ICU admission, patients requiring ventilator support had lower QFM levels than those requiring nasal prong or high-flow nasal cannula support. Those who died in the ICU had significantly lower QFM levels (4.0 IUs/mL) at ICU admission than those who survived (5.8 IUs/mL). Conclusions Reduced QFM levels among patients with severe ARF reflect impaired cellular immune responses and suggest that QFM may serve as a practical tool for early risk stratification and immune monitoring in ICU settings.

Objectives: Gastric dysplasia is primarily treated using endoscopic resection. Although argon plasma coagulation (APC) is an alternative treatment for older patients or those with bleeding tendencies, studies have reported a higher rate of local recurrence after APC than after endoscopic resection. Using pathological examinations, this study aimed to investigate the incidence and associated causative factors of residual dysplasia following APC. Methods: This prospective study recruited patients with low-grade gastric dysplasia from March 2020 to February 2021 and conducted follow-up examinations for 15 months after enrollment of the last patient. The patients were randomly assigned to undergo APC at an output power setting of 45, 60, or 80 W. Results: Residual lesions were found in 13 of 68 patients (19.1%) during the 24-h follow-up endoscopy and biopsy. The Ki-67 index, a marker of cellular proliferation, was significantly associated with the presence of residual lesions. The presence of residual dysplasia at the three-month follow-up was associated with the presence of residual lesions at the 24-h follow-up and a positive Ki-67 index. Only three of the 13 patients with residual lesions 24 h after APC demonstrated residual lesions at the three-month follow up. No post-procedural complications were observed. Conclusions Residual dysplasia may persist even after APC and cause local recurrence. If Ki-67-positive cells are detected in the remnant tissue following APC, additional interventions should be considered.