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.

Objective: Recently, various mental health promotion programs using virtual reality (VR) technology have been tried in the psychiatric field. Considering the importance of mental health in pregnant women, VR-assisted mental health promotion programs for pregnant women are needed to be developed. This study aimed to prospectively investigate the efficacy of a VR-assisted mental health promotion program for pregnant women. Methods: Fifty-five pregnant women were participated in this study. Mental health states such as depression, anxiety, perceived stress, and quality of life were assessed by Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale, and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF) before and after using VR program treatment. Based on the mental health types of pregnant women classified by cluster analysis, the effects of the VR program were analyzed by paired t test and Wilcoxon signed rank test. Results: The VR program significantly reduced PHQ-9 (p = 0.033) and GAD-7 (p = 0.046) scores, and significantly increased WHOQOL-BREF (p = 0.026) score of the participants. Additionally, when classifying the mental health types of pregnant women, the VR program was significantly effective to improve depression, anxiety, and quality of life in the most severe group based on the cluster analysis. Conclusion The results of this study suggest that VR program may be effective to improve the mental health of pregnant women. Particularly, VR programs for the high-risk group of depression might be the most effective. Therefore, VR-assisted mental health promotion programs could be useful for managing the mental health in pregnant women.

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: Several real-world studies have been done in patients with nonvalvular atrial fibrillation (NVAF); however, information on its safety profile in patients with renal impairment is limited. XARENAL, a real-world study, aimed to prospectively investigate the safety profile of rivaroxaban in patients with NVAF with renal impairment (creatinine clearance [CrCl], 15–49 mL/min). Methods: XARENAL is an observational single-arm cohort study in renal impairment NVAF patients. Patients were followed up approximately every 3 months for 1 year or until 30 days following early discontinuation. The primary endpoint was major bleeding events. All adverse events, symptomatic thromboembolic events, treatment duration, and renal function change from baseline were the secondary endpoints. Results: XARENAL included 888 patients from 29 study sites. Overall, 713 (80.3%) had moderate renal impairment (CrCl, 30–49 mL/min), and 175 (19.7%) had severe renal impairment (CrCl, 15–29 mL/min) with a mean estimated glomerular filtration rate (eGFR) of 45.2±13.0 mL/min/1.73 m 2 . The mean risk scores were 3.3±1.4 and 1.7±0.9 for CHA 2 DS 2 -VASc score and HAS-BLED score, respectively. An incidence proportion of 5.6% (6.2 events per 100 patient-years) developed major bleeding; however, fatal bleeding occurred in 0.5% (0.5 events per 100 patient-years). The mean change in the eGFR was 2.22±26.47 mL/min/1.73 m 2 per year. Conclusions XARENAL observed no meaningful differences in major bleeding events from other previous findings as well as renal function changes in rivaroxaban-treated NVAF patients with renal impairment, which is considered to be acceptable in clinical practice.

Background and Objectives: Several real-world studies have been done in patients with nonvalvular atrial fibrillation (NVAF); however, information on its safety profile in patients with renal impairment is limited. XARENAL, a real-world study, aimed to prospectively investigate the safety profile of rivaroxaban in patients with NVAF with renal impairment (creatinine clearance [CrCl], 15–49 mL/min). Methods: XARENAL is an observational single-arm cohort study in renal impairment NVAF patients. Patients were followed up approximately every 3 months for 1 year or until 30 days following early discontinuation. The primary endpoint was major bleeding events. All adverse events, symptomatic thromboembolic events, treatment duration, and renal function change from baseline were the secondary endpoints. Results: XARENAL included 888 patients from 29 study sites. Overall, 713 (80.3%) had moderate renal impairment (CrCl, 30–49 mL/min), and 175 (19.7%) had severe renal impairment (CrCl, 15–29 mL/min) with a mean estimated glomerular filtration rate (eGFR) of 45.2±13.0 mL/min/1.73 m 2 . The mean risk scores were 3.3±1.4 and 1.7±0.9 for CHA 2 DS 2 -VASc score and HAS-BLED score, respectively. An incidence proportion of 5.6% (6.2 events per 100 patient-years) developed major bleeding; however, fatal bleeding occurred in 0.5% (0.5 events per 100 patient-years). The mean change in the eGFR was 2.22±26.47 mL/min/1.73 m 2 per year. Conclusions XARENAL observed no meaningful differences in major bleeding events from other previous findings as well as renal function changes in rivaroxaban-treated NVAF patients with renal impairment, which is considered to be acceptable in clinical practice.

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.