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 the era of precision medicine, pharmacogenetics has substantial potential for addressing inter-individual variability in drug responses. Although pharmacogenetics has been a research focus for many years, resulting in the establishment of several formal guidelines, its clinical implementation remains limited to several gene–drug combinations in most countries, including Korea. The main causes of delayed implementation are technical challenges in genotyping and knowledge gaps among healthcare providers; therefore, clinical laboratories play a critical role in the timely implementation of pharmacogenetics. This paper presents an update of the Clinical Pharmacogenetic Testing and Application guidelines issued by the Korean Society for Laboratory Medicine and aims to provide the necessary information for clinical laboratories planning to implement or expand their pharmacogenetic testing. Current knowledge regarding nomenclature, gene–drug relationships, genotyping technologies, testing strategies, methods for clinically relevant information delivery, QC, and reimbursements has been curated and described in this guideline.

Objective: Bipolar disorder (BD) is marked by significant change in mood and energy levels with sleep disturbance a common feature, resulting in diminished quality of life and impaired daily functioning. This study assessed the association between BD-polygenic risk scores (PRS) and hypnotics in bipolar I disorder (BD-I) patients. Methods: Large-sample data were collected from the genome-wide association study of a multicenter Bipolar Genomic Study, and 1,394 BD-I patients with available medication information were divided into two groups depending on whether they used hypnotics or not. The Diagnostic Interview for Genetic Studies (DIGS) score was used to assess the clinical manifestations and function of the participants and the association between the use of hypnotics and genetic risk was analyzed. Results: Of the 1,394 total participants, 556 (40%) patients received hypnotics, mostly benzodiazepines, administered singly or in combination with other sleeping agents such as, Z-drugs, melatonin-related drugs, and trazodone. The DIGS score was significantly higher for negative categories in the group prescribed hypnotics as was the BD-PRS score, according to the four p value thresholds (p = 0.3, 0.2, 0.1, and 0.05). Logistic regression analysis confirmed a statistically significant association between the BD-PRS and hypnotic use. Conclusion Our results suggest an association between hypnotic use and genetic susceptibility to BD. Sleep disturbances in participants were based on the prescription status of hypnotics supporting the hypothesis that sleep disturbances may be associated with genetic aspects of BD-I. Further genetic studies on genetic overlaps between BD and specific phenotypes or medication responses are required.

Objective: Bipolar disorder (BD) is marked by significant change in mood and energy levels with sleep disturbance a common feature, resulting in diminished quality of life and impaired daily functioning. This study assessed the association between BD-polygenic risk scores (PRS) and hypnotics in bipolar I disorder (BD-I) patients. Methods: Large-sample data were collected from the genome-wide association study of a multicenter Bipolar Genomic Study, and 1,394 BD-I patients with available medication information were divided into two groups depending on whether they used hypnotics or not. The Diagnostic Interview for Genetic Studies (DIGS) score was used to assess the clinical manifestations and function of the participants and the association between the use of hypnotics and genetic risk was analyzed. Results: Of the 1,394 total participants, 556 (40%) patients received hypnotics, mostly benzodiazepines, administered singly or in combination with other sleeping agents such as, Z-drugs, melatonin-related drugs, and trazodone. The DIGS score was significantly higher for negative categories in the group prescribed hypnotics as was the BD-PRS score, according to the four p value thresholds (p = 0.3, 0.2, 0.1, and 0.05). Logistic regression analysis confirmed a statistically significant association between the BD-PRS and hypnotic use. Conclusion Our results suggest an association between hypnotic use and genetic susceptibility to BD. Sleep disturbances in participants were based on the prescription status of hypnotics supporting the hypothesis that sleep disturbances may be associated with genetic aspects of BD-I. Further genetic studies on genetic overlaps between BD and specific phenotypes or medication responses are required.

Objective: Bipolar disorder (BD) is marked by significant change in mood and energy levels with sleep disturbance a common feature, resulting in diminished quality of life and impaired daily functioning. This study assessed the association between BD-polygenic risk scores (PRS) and hypnotics in bipolar I disorder (BD-I) patients. Methods: Large-sample data were collected from the genome-wide association study of a multicenter Bipolar Genomic Study, and 1,394 BD-I patients with available medication information were divided into two groups depending on whether they used hypnotics or not. The Diagnostic Interview for Genetic Studies (DIGS) score was used to assess the clinical manifestations and function of the participants and the association between the use of hypnotics and genetic risk was analyzed. Results: Of the 1,394 total participants, 556 (40%) patients received hypnotics, mostly benzodiazepines, administered singly or in combination with other sleeping agents such as, Z-drugs, melatonin-related drugs, and trazodone. The DIGS score was significantly higher for negative categories in the group prescribed hypnotics as was the BD-PRS score, according to the four p value thresholds (p = 0.3, 0.2, 0.1, and 0.05). Logistic regression analysis confirmed a statistically significant association between the BD-PRS and hypnotic use. Conclusion Our results suggest an association between hypnotic use and genetic susceptibility to BD. Sleep disturbances in participants were based on the prescription status of hypnotics supporting the hypothesis that sleep disturbances may be associated with genetic aspects of BD-I. Further genetic studies on genetic overlaps between BD and specific phenotypes or medication responses are required.

Objective: Bipolar disorder (BD) is marked by significant change in mood and energy levels with sleep disturbance a common feature, resulting in diminished quality of life and impaired daily functioning. This study assessed the association between BD-polygenic risk scores (PRS) and hypnotics in bipolar I disorder (BD-I) patients. Methods: Large-sample data were collected from the genome-wide association study of a multicenter Bipolar Genomic Study, and 1,394 BD-I patients with available medication information were divided into two groups depending on whether they used hypnotics or not. The Diagnostic Interview for Genetic Studies (DIGS) score was used to assess the clinical manifestations and function of the participants and the association between the use of hypnotics and genetic risk was analyzed. Results: Of the 1,394 total participants, 556 (40%) patients received hypnotics, mostly benzodiazepines, administered singly or in combination with other sleeping agents such as, Z-drugs, melatonin-related drugs, and trazodone. The DIGS score was significantly higher for negative categories in the group prescribed hypnotics as was the BD-PRS score, according to the four p value thresholds (p = 0.3, 0.2, 0.1, and 0.05). Logistic regression analysis confirmed a statistically significant association between the BD-PRS and hypnotic use. Conclusion Our results suggest an association between hypnotic use and genetic susceptibility to BD. Sleep disturbances in participants were based on the prescription status of hypnotics supporting the hypothesis that sleep disturbances may be associated with genetic aspects of BD-I. Further genetic studies on genetic overlaps between BD and specific phenotypes or medication responses are required.

Purpose: This study aimed to explore how autonomy support mediates the association between exercise knowledge and exercise self-efficacy in patients with severe mental illness. Methods: A total of 181 individuals were selected through convenience sampling. They completed self-administered surveys measuring exercise knowledge, autonomy support, and exercise self-efficacy. The data analysis was conducted using descriptive statistics, t-tests, one-way analysis of variance, Pearson’s correlation coefficients, and multiple linear regression. To determine the statistical significance of the mediating effect, a bootstrapping test was also conducted. Results: This research revealed that autonomy support significantly predicted exercise self-efficacy and partially mediated the association between exercise knowledge and exercise self-efficacy (lower limit confidence interval [LLCI]: 2.34; upper limit confidence interval [ULCI]: 5.97). The model incorporating exercise knowledge and autonomy support explained 42.0% of the variance in exercise self-efficacy. Conclusion Collaborative endeavors involving mental health practitioners and exercise experts demonstrate notable efficacy in enhancing exercise self-efficacy of individuals with mental illness.