Limited data exist regarding the real-world practices and clinical outcomes in patients with ischemic heart failure with reduced left ventricular ejection fractions (LVEFs).Using nationwide registry data from South Korea, we aimed to investigate long-term outcomes and clinical practices, especially implantable cardioverter defibrillators (ICDs) implantation, in patients with reduced LVEFs at least 40 days after acute myocardial infarction (AMI). Of 13,056 patients with AMI between 2011 and 2015, we analyzed 350 (median age, 66 years [interquartile range, 56-75]) who had LVEFs <40% on follow-up transthoracic echocardiogram 40 days after the index event. The primary outcome was cardiac-cause mortality at 3 years. Secondary outcomes comprised major cardiovascular events as well as outcomes defined by the use of ICDs, cardiac resynchronization therapy defibrillators (CRT-Ds), and electrophysiology studies. Among 350 patients, 39 (11.1%) died from cardiac causes during 3 years of follow-up. Eleven (3.1%) were hospitalized for ventricular tachycardia. The rate of ICD or CRT-D implantation up to 3 years was 5.7% (20/350). Cox time-to-event analysis revealed older age, LVEF <30%, diabetes mellitus, and previous MI or revascularization as positively associated with cardiac death, whereas the use of statins and body weight <67 kg were negatively associated. This nationwide Korean registry demonstrated that only 5.7% of patients who had reduced LVEFs after 40 days of AMI underwent ICD implantations over 3 years. Considering the high mortality, concerted efforts are needed to improve clinical outcomes for patients who may have been candidates for ICD implantation.

The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

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.

Total laboratory automation (TLA) is a transformative solution in clinical laboratories that addresses growing demands for operational efficiency, accuracy, and rapid turnaround times in patient care. TLA integrates advanced technologies across pre-analytical, analytical, and post-analytical phases, thereby streamlining workflows, reducing manual intervention, and enhancing QC. TLA adoption is driven by factors such as increasing test volumes, the need for cost reduction and regulatory compliance, and labor shortages. Key benefits of TLA include improved accuracy through error minimization, optimized resource utilization, enhanced staff well-being, and consistent delivery of high-quality results. Leading companies, including Abbott, Roche, Siemens, and Beckman Coulter, dominate the global TLA market with innovative solutions. Recent developments incorporate artificial intelligence (AI), machine learning, robotics, and Internet-of-things technologies, which enable predictive analytics and automated data management. However, challenges remain, including high implementation costs, the need for workforce training, cybersecurity concerns, and system integration complexities. Future trends indicate that TLA will advance through enhanced AI integration, sustainable practices, and big data analytics, fostering continuous improvements in precision diagnostics and clinical outcomes. Moreover, TLA has the potential to revolutionize laboratory operations globally, driving efficiency, accuracy, and sustainability while ultimately improving patient care. Successful adoption of TLA will require strategic planning, interdisciplinary collaboration, and alignment with emerging healthcare needs. In this review, we emphasize that overcoming these challenges through innovation and robust management is essential for ensuring that TLA continues to play a vital role in modern healthcare systems.

Background: Citrin deficiency is an autosomal recessive disorder caused by pathogenic variants in SLC25A13, presenting with various age-dependent clinical phenotypes and a broad spectrum of severity. However, few studies have examined the frequency and prevalence of citrin deficiency. We aimed to analyze the carrier frequency and disease prevalence in East Asian populations and Koreans. Methods: We comprehensively reviewed the literature and conducted a cross-sectional study to analyze genomic databases, including the Genome Aggregation Database (gnomAD), Korean Variant Archive (KOVA), and Tohoku Medical Megabank Organization (ToMMo), to identify pathogenic SLC25A13 variants in East Asian populations. A founder 3-kilobase (kb) insertion in intron 16 of SLC25A13 was investigated using whole-genome sequencing data from 681 Koreans with the Linux grep command. Results: Twenty-three pathogenic SLC25A13 variants were identified, with c.852_855del being the most common. Analysis of data from 17,501 East Asian individuals in the gnomAD and ToMMo databases revealed a carrier frequency of 1 in 62 people. Analysis of data from 7,214 individuals in the gnomAD and KOVA databases revealed a carrier frequency of 1 in 86, corresponding to an estimated disease prevalence of 1 in 29,502.c.1177+1G > A was identified as the most prevalent pathogenic variant in Koreans. The 3 kb insertion in intron 16 was detected in three out of 681 individuals, indicating a carrier frequency of 1 in 228. Conclusions The high carrier frequency of citrin deficiency in East Asians highlights the need for enhanced genetic screening and counseling, particularly in Korea, providing a valuable reference for future studies on genetic diversity and pathogenic variants in this population.

Background: Humans are exposed to mercury primarily in its highly toxic form, methyl mercury, which is known to have adverse effects on various organs and systems. The negative impact of mercury exposure on the growth, development, and mental health of children, from infancy to adolescence, is well-documented. However, there are no internationally standardized safe limits for mercury exposure. This study investigated the impact of dietary habits and higher body mass index (BMI) on blood mercury levels in adolescents. Methods: This study analyzed the data from the 4th Korean National Environmental Health Survey (KoNEHS) 2018–2020. The focus was on 825 middle and high school students aged 13–18 years, whose blood mercury levels were measured. A survey on dietary and lifestyle habits was also conducted. Blood mercury levels were categorized by geometric median values, and associations with overweight status and seafood consumption were examined using a generalized linear model. Results: The geometric mean blood mercury level for the entire sample was 1.37 μg/L, with levels of 1.31 μg/L in normal-weight individuals and 1.43 μg/L in overweight individuals, showing a statistically significant difference between the two groups. After adjusting for other variables, blood mercury levels were significantly associated with overweight status (estimate: 0.084; p = 0.018; 95% confidence interval [CI]: 0.015–0.153), consumption of large fish and tuna more than once a week (estimate: 0.18; p = 0.001; 95% CI: 0.077–0.284), and consumption of fish once a week or more (estimate: 0.147; p = 0.004; 95% CI: 0.043–0.250). Conclusions In adolescents, a higher BMI and an increased consumption of large fish, tuna, and fish were associated with higher blood mercury levels. Notably, a stronger association was found between large fish consumption and blood mercury levels in the overweight group. These findings suggest the need to moderate seafood consumption and establish more proactive mercury exposure standards for adolescents.

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.